remove results files, make Paper hashable, add dump jsonl methods, make uniq search

.gitignore

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 .coverage
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results/arxiv-ee-paper-list.md

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-- [ ] [CS.CL , CS.AI , CS.LG, 2023] [Syntactically Robust Training on Partially-Observed Data for Open Information Extraction](http://arxiv.org/abs/2301.06841v1)
-- [ ] [CS.CL, 2023] [tieval: An Evaluation Framework for Temporal Information Extraction Systems](http://arxiv.org/abs/2301.04643v1)
-- [ ] [CS.CL, 2023] [Universal Information Extraction as Unified Semantic Matching](http://arxiv.org/abs/2301.03282v1)
-- [ ] [CS.CL, 2023] [Mask-then-Fill: A Flexible and Effective Data Augmentation Framework for Event Extraction](http://arxiv.org/abs/2301.02427v1)
-- [ ] [CS.CL , CS.AI, 2023] [PIE-QG: Paraphrased Information Extraction for Unsupervised Question Generation from Small Corpora](http://arxiv.org/abs/2301.01064v1)
-- [ ] [CS.CL , CS.AI, 2022] [Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset](http://arxiv.org/abs/2209.13464v2)
-- [ ] [CS.CL, 2022] [Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notes](http://arxiv.org/abs/2209.09485v1)
-- [ ] [CS.CL, 2022] [A Few-shot Approach to Resume Information Extraction via Prompts](http://arxiv.org/abs/2209.09450v1)
-- [ ] [CS.CL, 2022] [Automatic Error Analysis for Document-level Information Extraction](http://arxiv.org/abs/2209.07442v1)
-- [ ] [CS.CL, 2022] [OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction](http://arxiv.org/abs/2209.02693v1)
-- [ ] [CS.CL, 2022] [Few-Shot Document-Level Event Argument Extraction](http://arxiv.org/abs/2209.02203v1)
-- [ ] [CS.CL, 2022] [Few-Shot Document-Level Event Argument Extraction](http://arxiv.org/abs/2209.02203v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [Multi-Scale Contrastive Co-Training for Event Temporal Relation Extraction](http://arxiv.org/abs/2209.00568v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [Multi-Scale Contrastive Co-Training for Event Temporal Relation Extraction](http://arxiv.org/abs/2209.00568v1)
-- [ ] [CS.CL, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](http://arxiv.org/abs/2208.13017v3)
-- [ ] [CS.CL, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](http://arxiv.org/abs/2208.13017v3)
-- [ ] [CS.CL , CS.AI, 2022] [SPOT: Knowledge-Enhanced Language Representations for Information Extraction](http://arxiv.org/abs/2208.09625v2)
-- [ ] [CS.CL , CS.AI, 2022] [End-to-end Clinical Event Extraction from Chinese Electronic Health Record](http://arxiv.org/abs/2208.09354v1)
-- [ ] [CS.CL, 2022] [Open Information Extraction from 2007 to 2022 -- A Survey](http://arxiv.org/abs/2208.08690v1)
-- [ ] [CS.AI , CS.CL , CS.IR, 2022] [NECE: Narrative Event Chain Extraction Toolkit](http://arxiv.org/abs/2208.08063v3)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [DICE: Data-Efficient Clinical Event Extraction with Generative Models](http://arxiv.org/abs/2208.07989v1)
-- [ ] [CS.CL, 2022] [Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features](http://arxiv.org/abs/2208.04011v1)
-- [ ] [CS.CL , CS.MM, 2022] [Layout-Aware Information Extraction for Document-Grounded Dialogue: Dataset, Method and Demonstration](http://arxiv.org/abs/2207.06717v1)
-- [ ] [CS.CL, 2022] [GMN: Generative Multi-modal Network for Practical Document Information Extraction](http://arxiv.org/abs/2207.04713v1)
-- [ ] [CS.CL, 2022] [A Medical Information Extraction Workbench to Process German Clinical Text](http://arxiv.org/abs/2207.03885v2)
-- [ ] [CS.CL, 2022] [DetIE: Multilingual Open Information Extraction Inspired by Object Detection](http://arxiv.org/abs/2206.12514v1)
-- [ ] [CS.CL , CS.IR, 2022] [Unsupervised Key Event Detection from Massive Text Corpora](http://arxiv.org/abs/2206.04153v2)
-- [ ] [CS.CL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](http://arxiv.org/abs/2206.03377v1)
-- [ ] [CS.CL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](http://arxiv.org/abs/2206.03377v1)
-- [ ] [CS.CL , CS.DL, 2022] [Plumber: A Modular Framework to Create Information Extraction Pipelines](http://arxiv.org/abs/2206.01442v1)
-- [ ] [CS.CL, 2022] [EA$^2$E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](http://arxiv.org/abs/2205.14847v1)
-- [ ] [CS.CL, 2022] [EA$^2$E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](http://arxiv.org/abs/2205.14847v1)
-- [ ] [CS.CL , CS.AI, 2022] [Jointly Learning Span Extraction and Sequence Labeling for Information Extraction from Business Documents](http://arxiv.org/abs/2205.13434v1)
-- [ ] [CS.CL, 2022] [GENEVA: Pushing the Limit of Generalizability for Event Argument Extraction with 100+ Event Types](http://arxiv.org/abs/2205.12505v1)
-- [ ] [CS.CL, 2022] [GENEVA: Pushing the Limit of Generalizability for Event Argument Extraction with 100+ Event Types](http://arxiv.org/abs/2205.12505v1)
-- [ ] [CS.CL , CS.AI, 2022] [Improve Event Extraction via Self-Training with Gradient Guidance](http://arxiv.org/abs/2205.12490v1)
-- [ ] [CS.CL, 2022] [A Survey on Neural Open Information Extraction: Current Status and Future Directions](http://arxiv.org/abs/2205.11725v2)
-- [ ] [CS.CL , CS.AI, 2022] [Dynamic Prefix-Tuning for Generative Template-based Event Extraction](http://arxiv.org/abs/2205.06166v1)
-- [ ] [CS.CL , CS.LG, 2022] [Utilizing coarse-grained data in low-data settings for event extraction](http://arxiv.org/abs/2205.05468v1)
-- [ ] [CS.CL, 2022] [CompactIE: Compact Facts in Open Information Extraction](http://arxiv.org/abs/2205.02880v2)
-- [ ] [CS.CL , CS.DL , H.4, 2022] [A Library Perspective on Nearly-Unsupervised Information Extraction Workflows in Digital Libraries](http://arxiv.org/abs/2205.00716v1)
-- [ ] [CS.CL , CS.IR, 2022] [Large-Scale Multi-Document Summarization with Information Extraction and Compression](http://arxiv.org/abs/2205.00548v1)
-- [ ] [CS.CL, 2022] [CUP: Curriculum Learning based Prompt Tuning for Implicit Event Argument Extraction](http://arxiv.org/abs/2205.00498v2)
-- [ ] [CS.CL, 2022] [CUP: Curriculum Learning based Prompt Tuning for Implicit Event Argument Extraction](http://arxiv.org/abs/2205.00498v2)
-- [ ] [CS.CL , CS.AI, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](http://arxiv.org/abs/2205.00241v1)
-- [ ] [CS.CL , CS.AI, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](http://arxiv.org/abs/2205.00241v1)
-- [ ] [CS.CL , 68T99 , I.2.7, 2022] [CrudeOilNews: An Annotated Crude Oil News Corpus for Event Extraction](http://arxiv.org/abs/2204.03871v1)
-- [ ] [CS.CL , CS.AI, 2022] [Improving Zero-Shot Event Extraction via Sentence Simplification](http://arxiv.org/abs/2204.02531v1)
-- [ ] [CS.CL, 2022] [ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations](http://arxiv.org/abs/2203.13602v3)
-- [ ] [CS.CL, 2022] [Unified Structure Generation for Universal Information Extraction](http://arxiv.org/abs/2203.12277v1)
-- [ ] [CS.CL , CS.CV , CS.LG, 2022] [FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction](http://arxiv.org/abs/2203.08411v2)
-- [ ] [CS.CL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](http://arxiv.org/abs/2203.08308v1)
-- [ ] [CS.CL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](http://arxiv.org/abs/2203.08308v1)
-- [ ] [CS.CL , CS.AI, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](http://arxiv.org/abs/2202.12109v2)
-- [ ] [CS.CL , CS.AI, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](http://arxiv.org/abs/2202.12109v2)
-- [ ] [CS.CL, 2022] [FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction](http://arxiv.org/abs/2202.08316v2)
-- [ ] [STAT.AP , CS.CL, 2022] [Introducing the ICBe Dataset: Very High Recall and Precision Event Extraction from Narratives about International Crises](http://arxiv.org/abs/2202.07081v2)
-- [ ] [CS.CL, 2022] [Document-Level Event Extraction via Human-Like Reading Process](http://arxiv.org/abs/2202.03092v1)
-- [ ] [CS.CL, 2022] [WebFormer: The Web-page Transformer for Structure Information Extraction](http://arxiv.org/abs/2202.00217v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [On Event Individuation for Document-Level Information Extraction](http://arxiv.org/abs/2212.09702v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [On Event Individuation for Document-Level Information Extraction](http://arxiv.org/abs/2212.09702v1)
-- [ ] [CS.CL, 2022] [Joint Information Extraction with Cross-Task and Cross-Instance High-Order Modeling](http://arxiv.org/abs/2212.08929v1)
-- [ ] [CS.CL , CS.IR, 2022] [MORTY: Structured Summarization for Targeted Information Extraction from Scholarly Articles](http://arxiv.org/abs/2212.05429v1)
-- [ ] [CS.CL , COND-MAT.MTRL-SCI , I.7.M, 2022] [Structured information extraction from complex scientific text with fine-tuned large language models](http://arxiv.org/abs/2212.05238v1)
-- [ ] [CS.CL , CS.AI, 2022] [Syntactic Multi-view Learning for Open Information Extraction](http://arxiv.org/abs/2212.02068v1)
-- [ ] [CS.CL, 2022] [Towards Generalized Open Information Extraction](http://arxiv.org/abs/2211.15987v1)
-- [ ] [CS.CL, 2022] [MUSIED: A Benchmark for Event Detection from Multi-Source Heterogeneous Informal Texts](http://arxiv.org/abs/2211.13896v1)
-- [ ] [CS.CL, 2022] [PESE: Event Structure Extraction using Pointer Network based Encoder-Decoder Architecture](http://arxiv.org/abs/2211.12157v1)
-- [ ] [CS.CL, 2022] [MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction](http://arxiv.org/abs/2211.07342v1)
-- [ ] [CS.CL, 2022] [MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction](http://arxiv.org/abs/2211.07342v1)
-- [ ] [CS.CL, 2022] [Retrieval-Augmented Generative Question Answering for Event Argument Extraction](http://arxiv.org/abs/2211.07067v1)
-- [ ] [CS.CL, 2022] [Retrieval-Augmented Generative Question Answering for Event Argument Extraction](http://arxiv.org/abs/2211.07067v1)
-- [ ] [CS.CL , CS.AI , CS.IR , CS.LG, 2022] [TIER-A: Denoising Learning Framework for Information Extraction](http://arxiv.org/abs/2211.11527v1)
-- [ ] [CS.CL , CS.AI, 2022] [Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction](http://arxiv.org/abs/2211.06014v2)
-- [ ] [CS.CL, 2022] [MEE: A Novel Multilingual Event Extraction Dataset](http://arxiv.org/abs/2211.05955v2)
-- [ ] [CS.CL, 2022] [Efficient Zero-shot Event Extraction with Context-Definition Alignment](http://arxiv.org/abs/2211.05156v2)
-- [ ] [CS.CL, 2022] [1Cademy @ Causal News Corpus 2022: Leveraging Self-Training in Causality Classification of Socio-Political Event Data](http://arxiv.org/abs/2211.02729v1)
-- [ ] [CS.CV , CS.CL, 2022] [Video Event Extraction via Tracking Visual States of Arguments](http://arxiv.org/abs/2211.01781v2)
-- [ ] [CS.CV , CS.CL, 2022] [Video Event Extraction via Tracking Visual States of Arguments](http://arxiv.org/abs/2211.01781v2)
-- [ ] [CS.CL, 2022] [Data-efficient End-to-end Information Extraction for Statistical Legal Analysis](http://arxiv.org/abs/2211.01692v1)
-- [ ] [CS.CL, 2022] [Open-Vocabulary Argument Role Prediction for Event Extraction](http://arxiv.org/abs/2211.01577v1)
-- [ ] [CS.CL, 2022] [Open-Vocabulary Argument Role Prediction for Event Extraction](http://arxiv.org/abs/2211.01577v1)
-- [ ] [CS.CL, 2022] [Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset](http://arxiv.org/abs/2211.00869v1)
-- [ ] [CS.CL, 2022] [Bi-Directional Iterative Prompt-Tuning for Event Argument Extraction](http://arxiv.org/abs/2210.15843v1)
-- [ ] [CS.CL, 2022] [Bi-Directional Iterative Prompt-Tuning for Event Argument Extraction](http://arxiv.org/abs/2210.15843v1)
-- [ ] [CS.CL, 2022] [CrisisLTLSum: A Benchmark for Local Crisis Event Timeline Extraction and Summarization](http://arxiv.org/abs/2210.14190v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2022] [IELM: An Open Information Extraction Benchmark for Pre-Trained Language Models](http://arxiv.org/abs/2210.14128v1)
-- [ ] [CS.CL, 2022] [PHEE: A Dataset for Pharmacovigilance Event Extraction from Text](http://arxiv.org/abs/2210.12560v1)
-- [ ] [CS.CL, 2022] [Schema-aware Reference as Prompt Improves Data-Efficient Relational Triple and Event Extraction](http://arxiv.org/abs/2210.10709v3)
-- [ ] [CS.CL, 2022] [EventGraph at CASE 2021 Task 1: A General Graph-based Approach to Protest Event Extraction](http://arxiv.org/abs/2210.09770v1)
-- [ ] [CS.CL, 2022] [EventGraph: Event Extraction as Semantic Graph Parsing](http://arxiv.org/abs/2210.08646v1)
-- [ ] [CS.CV , CS.CL, 2022] [Cross-domain Variational Capsules for Information Extraction](http://arxiv.org/abs/2210.09053v1)
-- [ ] [CS.CL, 2022] [Iterative Document-level Information Extraction via Imitation Learning](http://arxiv.org/abs/2210.06600v1)
-- [ ] [CS.CL , CS.AI, 2022] [Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction](http://arxiv.org/abs/2210.04992v2)
-- [ ] [CS.CL , CS.AI, 2022] [Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction](http://arxiv.org/abs/2210.04992v2)
-- [ ] [CS.CL , CS.LG, 2022] [HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crisis Response](http://arxiv.org/abs/2210.04573v3)
-- [ ] [CS.CL , CS.AI, 2022] [Causal Intervention-based Prompt Debiasing for Event Argument Extraction](http://arxiv.org/abs/2210.01561v1)
-- [ ] [CS.CL , CS.AI, 2022] [Causal Intervention-based Prompt Debiasing for Event Argument Extraction](http://arxiv.org/abs/2210.01561v1)
-- [ ] [CS.CL , CS.LG, 2022] [POTATO: exPlainable infOrmation exTrAcTion framewOrk](http://arxiv.org/abs/2201.13230v2)
-- [ ] [CS.CL , CS.IR, 2022] [Information Extraction through AI techniques: The KIDs use case at CONSOB](http://arxiv.org/abs/2202.01178v1)
-- [ ] [CS.CL , CS.IR , CS.LG, 2022] [From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction](http://arxiv.org/abs/2202.00475v1)
-- [ ] [CS.CL, 2022] [Writing Style Aware Document-level Event Extraction](http://arxiv.org/abs/2201.03188v1)
-- [ ] [CS.CL , CS.AI, 2022] [Monitoring Energy Trends through Automatic Information Extraction](http://arxiv.org/abs/2201.01559v1)
-- [ ] [CS.CL , COND-MAT.MTRL-SCI, 2021] [MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extraction](http://arxiv.org/abs/2109.15290v1)
-- [ ] [CS.CL , CS.AI , I.7; H.4; H.5, 2021] [Effective Use of Graph Convolution Network and Contextual Sub-Tree forCommodity News Event Extraction](http://arxiv.org/abs/2109.12781v1)
-- [ ] [CS.CL, 2021] [Language Model Priming for Cross-Lingual Event Extraction](http://arxiv.org/abs/2109.12383v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2021] [Zero-Shot Information Extraction as a Unified Text-to-Triple Translation](http://arxiv.org/abs/2109.11171v1)
-- [ ] [CS.CL, 2021] [Modality and Negation in Event Extraction](http://arxiv.org/abs/2109.09393v1)
-- [ ] [CS.CL , CS.IR , CS.LG, 2021] [Slot Filling for Biomedical Information Extraction](http://arxiv.org/abs/2109.08564v2)
-- [ ] [CS.AI , CS.CL, 2021] [An Ontology-Based Information Extraction System for Residential Land Use Suitability Analysis](http://arxiv.org/abs/2109.07672v1)
-- [ ] [CS.CL, 2021] [AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark](http://arxiv.org/abs/2109.07464v2)
-- [ ] [CS.CL, 2021] [Enhancing Clinical Information Extraction with Transferred Contextual Embeddings](http://arxiv.org/abs/2109.07243v2)
-- [ ] [CS.CL , CS.AI, 2021] [BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation](http://arxiv.org/abs/2109.06850v2)
-- [ ] [CS.CL, 2021] [Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction](http://arxiv.org/abs/2109.06798v1)
-- [ ] [CS.CL, 2021] [A system for information extraction from scientific texts in Russian](http://arxiv.org/abs/2109.06703v1)
-- [ ] [CS.CL , CS.CV, 2021] [Deep learning-based NLP Data Pipeline for EHR Scanned Document Information Extraction](http://arxiv.org/abs/2110.11864v1)
-- [ ] [CS.CL, 2021] [Traffic Event Detection as a Slot Filling Problem](http://arxiv.org/abs/2109.06035v1)
-- [ ] [Q-BIO.QM , CS.CL , CS.LG, 2021] [Clinical Trial Information Extraction with BERT](http://arxiv.org/abs/2110.10027v1)
-- [ ] [CS.CL, 2021] [Uncovering Main Causalities for Long-tailed Information Extraction](http://arxiv.org/abs/2109.05213v1)
-- [ ] [CS.CL , CS.AI, 2021] [PoKE: A Prompt-based Knowledge Eliciting Approach for Event Argument Extraction](http://arxiv.org/abs/2109.05190v3)
-- [ ] [CS.CL , CS.AI, 2021] [PoKE: A Prompt-based Knowledge Eliciting Approach for Event Argument Extraction](http://arxiv.org/abs/2109.05190v3)
-- [ ] [CS.CL, 2021] [Text-to-Table: A New Way of Information Extraction](http://arxiv.org/abs/2109.02707v2)
-- [ ] [CS.CL , CS.IR , CS.LG, 2021] [Knowledge Graph Enhanced Event Extraction in Financial Documents](http://arxiv.org/abs/2109.02592v1)
-- [ ] [CS.CL , CS.AI, 2021] [DEGREE: A Data-Efficient Generation-Based Event Extraction Model](http://arxiv.org/abs/2108.12724v3)
-- [ ] [CS.CL, 2021] [Event Extraction by Associating Event Types and Argument Roles](http://arxiv.org/abs/2108.10038v2)
-- [ ] [CS.CL, 2021] [Event Extraction by Associating Event Types and Argument Roles](http://arxiv.org/abs/2108.10038v2)
-- [ ] [CS.CL , CS.AI, 2021] [An Effective System for Multi-format Information Extraction](http://arxiv.org/abs/2108.06957v1)
-- [ ] [CS.CL, 2021] [BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents](http://arxiv.org/abs/2108.04539v5)
-- [ ] [CS.CL , CS.LG, 2021] [COfEE: A Comprehensive Ontology for Event Extraction from text](http://arxiv.org/abs/2107.10326v3)
-- [ ] [CS.CL , CS.AI, 2021] [An artificial intelligence natural language processing pipeline for information extraction in neuroradiology](http://arxiv.org/abs/2107.10021v1)
-- [ ] [CS.CL , CS.HC, 2021] [A Dialogue-based Information Extraction System for Medical Insurance Assessment](http://arxiv.org/abs/2107.05866v1)
-- [ ] [CS.CL, 2021] [CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction](http://arxiv.org/abs/2107.01583v1)
-- [ ] [CS.CL, 2021] [Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations](http://arxiv.org/abs/2106.12384v2)
-- [ ] [CS.CL, 2021] [Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations](http://arxiv.org/abs/2106.12384v2)
-- [ ] [CS.CL , CS.IR, 2021] [Deep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter](http://arxiv.org/abs/2106.11403v1)
-- [ ] [CS.CL , CS.LG, 2021] [ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction](http://arxiv.org/abs/2106.10786v1)
-- [ ] [CS.CL, 2021] [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](http://arxiv.org/abs/2106.09232v1)
-- [ ] [CS.CL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](http://arxiv.org/abs/2106.08629v1)
-- [ ] [CS.CL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](http://arxiv.org/abs/2106.08629v1)
-- [ ] [CS.CL , CS.GR, 2021] [Visualization Techniques to Enhance Automated Event Extraction](http://arxiv.org/abs/2106.06588v1)
-- [ ] [CS.CL, 2021] [Key Information Extraction From Documents: Evaluation And Generator](http://arxiv.org/abs/2106.14624v1)
-- [ ] [CS.DL , CS.CL, 2021] [CitationIE: Leveraging the Citation Graph for Scientific Information Extraction](http://arxiv.org/abs/2106.01560v1)
-- [ ] [CS.CL, 2021] [CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction](http://arxiv.org/abs/2106.00793v1)
-- [ ] [CS.CL , CS.AI, 2021] [Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker](http://arxiv.org/abs/2105.14924v1)
-- [ ] [CS.CL, 2021] [CLEVE: Contrastive Pre-training for Event Extraction](http://arxiv.org/abs/2105.14485v1)
-- [ ] [CS.CL , CS.CV , CS.LG, 2021] [ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents](http://arxiv.org/abs/2105.11672v1)
-- [ ] [CS.CL , CS.LG, 2021] [Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies](http://arxiv.org/abs/2105.08882v1)
-- [ ] [CS.CL , 68T99 , I.2.7, 2021] [An Annotated Commodity News Corpus for Event Extraction](http://arxiv.org/abs/2105.08214v3)
-- [ ] [CS.CL , CS.AI , CS.LG, 2021] [Doc2Dict: Information Extraction as Text Generation](http://arxiv.org/abs/2105.07510v2)
-- [ ] [CS.CL, 2021] [Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts](http://arxiv.org/abs/2105.05796v1)
-- [ ] [CS.CL, 2021] [Event Argument Extraction using Causal Knowledge Structures](http://arxiv.org/abs/2105.00477v1)
-- [ ] [CS.CL, 2021] [Event Argument Extraction using Causal Knowledge Structures](http://arxiv.org/abs/2105.00477v1)
-- [ ] [CS.CL, 2021] [Learning from Noisy Labels for Entity-Centric Information Extraction](http://arxiv.org/abs/2104.08656v2)
-- [ ] [CS.CL, 2021] [Cost-effective End-to-end Information Extraction for Semi-structured Document Images](http://arxiv.org/abs/2104.08041v2)
-- [ ] [CS.CL , CS.IR, 2021] [Event Detection as Question Answering with Entity Information](http://arxiv.org/abs/2104.06969v1)
-- [ ] [CS.CL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](http://arxiv.org/abs/2104.05919v1)
-- [ ] [CS.CL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](http://arxiv.org/abs/2104.05919v1)
-- [ ] [CS.CL , CS.IR, 2021] [Use of 'off-the-shelf' information extraction algorithms in clinical informatics: a feasibility study of MetaMap annotation of Italian medical notes](http://arxiv.org/abs/2104.00975v1)
-- [ ] [CS.CL, 2021] [PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation](http://arxiv.org/abs/2103.15075v1)
-- [ ] [CS.CL, 2021] [Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks](http://arxiv.org/abs/2103.09330v3)
-- [ ] [CS.CL , CS.AI , CS.LG, 2021] [DeepCPCFG: Deep Learning and Context Free Grammars for End-to-End Information Extraction](http://arxiv.org/abs/2103.05908v2)
-- [ ] [CS.CL, 2021] [Syntactic and Semantic-driven Learning for Open Information Extraction](http://arxiv.org/abs/2103.03448v1)
-- [ ] [CS.CL , CS.IR, 2021] [Better Call the Plumber: Orchestrating Dynamic Information Extraction Pipelines](http://arxiv.org/abs/2102.10966v1)
-- [ ] [CS.CL , CS.AI, 2021] [Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion](http://arxiv.org/abs/2102.09923v1)
-- [ ] [CS.CL , CS.AI , CS.IR , STAT.AP, 2021] [Syntactic-GCN Bert based Chinese Event Extraction](http://arxiv.org/abs/2112.09939v1)
-- [ ] [CS.CL , CS.LG , STAT.ML, 2021] [GenIE: Generative Information Extraction](http://arxiv.org/abs/2112.08340v3)
-- [ ] [CS.CL, 2021] [Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph](http://arxiv.org/abs/2112.06013v2)
-- [ ] [CS.CL , CS.AI , CS.IR , CS.LG, 2021] [Automated Drug-Related Information Extraction from French Clinical Documents: ReLyfe Approach](http://arxiv.org/abs/2112.11439v1)
-- [ ] [CS.CL , CS.AI, 2021] [Active Learning for Event Extraction with Memory-based Loss Prediction Model](http://arxiv.org/abs/2112.03073v1)
-- [ ] [CS.LG , CS.AI , CS.CL , ECON.GN , Q-FIN.EC , STAT.AP, 2021] [Forecasting Crude Oil Price Using Event Extraction](http://arxiv.org/abs/2111.09111v1)
-- [ ] [CS.IR , CS.AI , CS.CL, 2021] [Neural News Recommendation with Event Extraction](http://arxiv.org/abs/2111.05068v2)
-- [ ] [CS.CL , CS.AI , ECON.GN , Q-FIN.EC , STAT.AP, 2021] [American Hate Crime Trends Prediction with Event Extraction](http://arxiv.org/abs/2111.04951v1)
-- [ ] [CS.CL , CS.AI, 2021] [JaMIE: A Pipeline Japanese Medical Information Extraction System](http://arxiv.org/abs/2111.04261v1)
-- [ ] [CS.CL , CS.CV, 2021] [Information Extraction from Visually Rich Documents with Font Style Embeddings](http://arxiv.org/abs/2111.04045v2)
-- [ ] [CS.CL , CS.AI , CS.LG, 2021] [An overview of event extraction and its applications](http://arxiv.org/abs/2111.03212v1)
-- [ ] [CS.CL, 2021] [SERC: Syntactic and Semantic Sequence based Event Relation Classification](http://arxiv.org/abs/2111.02265v2)
-- [ ] [CS.CV , CS.AI , CS.CL, 2021] [BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network](http://arxiv.org/abs/2110.13683v1)
-- [ ] [CS.CV , CS.AI , CS.CL , CS.HC , CS.IR, 2021] [CoVA: Context-aware Visual Attention for Webpage Information Extraction](http://arxiv.org/abs/2110.12320v1)
-- [ ] [CS.CL , CS.AI, 2021] [milIE: Modular & Iterative Multilingual Open Information Extraction](http://arxiv.org/abs/2110.08144v2)
-- [ ] [CS.CL , CS.AI, 2021] [Making Document-Level Information Extraction Right for the Right Reasons](http://arxiv.org/abs/2110.07686v2)
-- [ ] [CS.CL , CS.AI, 2021] [Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding](http://arxiv.org/abs/2110.07476v2)
-- [ ] [CS.CL , CS.AI , CS.LG, 2021] [Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works](http://arxiv.org/abs/2110.04525v2)
-- [ ] [CS.CL, 2021] [Learning to Ask for Data-Efficient Event Argument Extraction](http://arxiv.org/abs/2110.00479v1)
-- [ ] [CS.CL, 2021] [Learning to Ask for Data-Efficient Event Argument Extraction](http://arxiv.org/abs/2110.00479v1)
-- [ ] [CS.CL , CS.AI, 2021] [LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction](http://arxiv.org/abs/2101.11177v1)
-- [ ] [CS.CL, 2020] [DWIE: an entity-centric dataset for multi-task document-level information extraction](http://arxiv.org/abs/2009.12626v2)
-- [ ] [CS.CL, 2020] [UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social Media](http://arxiv.org/abs/2009.10047v2)
-- [ ] [CS.CL , CS.AI, 2020] [Biomedical Event Extraction with Hierarchical Knowledge Graphs](http://arxiv.org/abs/2009.09335v3)
-- [ ] [CS.CL , CS.LG, 2020] [Multi$^2$OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT](http://arxiv.org/abs/2009.08128v2)
-- [ ] [CS.CL , CS.AI , 68T50, 68T01, 2020] [Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding](http://arxiv.org/abs/2009.07406v1)
-- [ ] [CS.CL , CS.AI, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](http://arxiv.org/abs/2009.07373v2)
-- [ ] [CS.CL , CS.AI, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](http://arxiv.org/abs/2009.07373v2)
-- [ ] [CS.CL, 2020] [Event Presence Prediction Helps Trigger Detection Across Languages](http://arxiv.org/abs/2009.07188v1)
-- [ ] [CS.CL, 2020] [GRIT: Generative Role-filler Transformers for Document-level Event Entity Extraction](http://arxiv.org/abs/2008.09249v2)
-- [ ] [CS.CL, 2020] [Tense, aspect and mood based event extraction for situation analysis and crisis management](http://arxiv.org/abs/2008.01555v1)
-- [ ] [CS.CL , CS.AI , CS.LG, 2020] [Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports](http://arxiv.org/abs/2008.01572v1)
-- [ ] [CS.CL, 2020] [Information Extraction of Clinical Trial Eligibility Criteria](http://arxiv.org/abs/2006.07296v6)
-- [ ] [CS.CL, 2020] [Unsupervised Label-aware Event Trigger and Argument Classification](http://arxiv.org/abs/2012.15243v2)
-- [ ] [CS.CL , CS.SI, 2020] [An Event Correlation Filtering Method for Fake News Detection](http://arxiv.org/abs/2012.05491v2)
-- [ ] [CS.CL , CS.LG, 2020] [Extracting COVID-19 Diagnoses and Symptoms From Clinical Text: A New Annotated Corpus and Neural Event Extraction Framework](http://arxiv.org/abs/2012.00974v2)
-- [ ] [CS.CL , I.2.7, 2020] [Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels](http://arxiv.org/abs/2011.08903v2)
-- [ ] [CS.LG , CS.CL, 2020] [Biomedical Information Extraction for Disease Gene Prioritization](http://arxiv.org/abs/2011.05188v2)
-- [ ] [CS.CL, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](http://arxiv.org/abs/2010.13391v1)
-- [ ] [CS.CL, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](http://arxiv.org/abs/2010.13391v1)
-- [ ] [CS.CL, 2020] [Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies](http://arxiv.org/abs/2010.12787v3)
-- [ ] [CS.CL, 2020] [Probing and Fine-tuning Reading Comprehension Models for Few-shot Event Extraction](http://arxiv.org/abs/2010.11325v1)
-- [ ] [CS.AI , CS.CL, 2020] [Explaining black-box text classifiers for disease-treatment information extraction](http://arxiv.org/abs/2010.10873v1)
-- [ ] [CS.CL , CS.IR, 2020] [FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents](http://arxiv.org/abs/2010.10755v1)
-- [ ] [CS.CL , CS.IR , CS.LG , I.2.7, 2020] [Learning from similarity and information extraction from structured documents](http://arxiv.org/abs/2011.07964v2)
-- [ ] [CS.CL , 60L10 , I.2.7, 2020] [Information Extraction from Swedish Medical Prescriptions with Sig-Transformer Encoder](http://arxiv.org/abs/2010.04897v1)
-- [ ] [CS.CL, 2020] [OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction](http://arxiv.org/abs/2010.03147v1)
-- [ ] [CS.CL, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](http://arxiv.org/abs/2010.03022v1)
-- [ ] [CS.CL, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](http://arxiv.org/abs/2010.03022v1)
-- [ ] [CS.CL, 2020] [GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction](http://arxiv.org/abs/2010.03009v2)
-- [ ] [CS.CL, 2020] [GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction](http://arxiv.org/abs/2010.03009v2)

results/dblp-ee-paper-list.md

@@ -1,13 +0,0 @@
-- [ ] [AAAI, 2022] [Learning to Ask for Data-Efficient Event Argument Extraction (Student Abstract).](https://ojs.aaai.org/index.php/AAAI/article/view/21686)
-- [ ] [AAAI, 2022] [Learning to Ask for Data-Efficient Event Argument Extraction (Student Abstract).](https://ojs.aaai.org/index.php/AAAI/article/view/21686)
-- [ ] [IJCAI, 2022] [Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph.](https://doi.org/10.24963/ijcai.2022/632)
-- [ ] [AAAI, 2021] [What the Role is vs. What Plays the Role: Semi-Supervised Event Argument Extraction via Dual Question Answering.](https://ojs.aaai.org/index.php/AAAI/article/view/17720)
-- [ ] [AAAI, 2021] [What the Role is vs. What Plays the Role: Semi-Supervised Event Argument Extraction via Dual Question Answering.](https://ojs.aaai.org/index.php/AAAI/article/view/17720)
-- [ ] [AAAI, 2018] [Scale Up Event Extraction Learning via Automatic Training Data Generation.](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16119)
-- [ ] [AAAI, 2016] [Joint Inference over a Lightly Supervised Information Extraction Pipeline: Towards Event Coreference Resolution for Resource-Scarce Languages.](http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12413)
-- [ ] [AAAI, 2016] [Joint Inference over a Lightly Supervised Information Extraction Pipeline: Towards Event Coreference Resolution for Resource-Scarce Languages.](http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12413)
-- [ ] [AAAI FALL SYMPOSIA, 2014] [Risk Event and Probability Extraction for Modeling Medical Risks.](http://www.aaai.org/ocs/index.php/FSS/FSS14/paper/view/9198)
-- [ ] [SIGIR, 2014] [An event extraction model based on timeline and user analysis in Latent Dirichlet allocation.](https://doi.org/10.1145/2600428.2609541)
-- [ ] [IJCAI, 2013] [Joint Modeling of Argument Identification and Role Determination in Chinese Event Extraction with Discourse-Level Information.](http://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6285)
-- [ ] [IJCAI, 2013] [Joint Modeling of Argument Identification and Role Determination in Chinese Event Extraction with Discourse-Level Information.](http://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6285)
-- [ ] [AAAI, 2008] [Combining Global Relevance Information with Local Contextual Clues for Event-Oriented Information Extraction.](http://www.aaai.org/Library/AAAI/2008/aaai08-321.php)

results/doc-paper-list.md

@@ -1,117 +0,0 @@
-- [ ] [FINDINGS, 2022] [ArgGen: Prompting Text Generation Models for Document-Level Event-Argument Aggregation](https://aclanthology.org/2022.findings-aacl.37)
-- [ ] [COLING, 2022] [Key Mention Pairs Guided Document-Level Relation Extraction](https://aclanthology.org/2022.coling-1.165)
-- [ ] [COLING, 2022] [Document-level Biomedical Relation Extraction Based on Multi-Dimensional Fusion Information and Multi-Granularity Logical Reasoning](https://aclanthology.org/2022.coling-1.183)
-- [ ] [COLING, 2022] [ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification](https://aclanthology.org/2022.coling-1.185)
-- [ ] [COLING, 2022] [Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning](https://aclanthology.org/2022.coling-1.213)
-- [ ] [COLING, 2022] [CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction](https://aclanthology.org/2022.coling-1.221)
-- [ ] [COLING, 2022] [Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning](https://aclanthology.org/2022.coling-1.231)
-- [ ] [COLING, 2022] [CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine Translation](https://aclanthology.org/2022.coling-1.462)
-- [ ] [FINDINGS, 2022] [DOCmT5: Document-Level Pretraining of Multilingual Language Models](https://aclanthology.org/2022.findings-naacl.32)
-- [ ] [FINDINGS, 2022] [Learn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation](https://aclanthology.org/2022.findings-naacl.105)
-- [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
-- [ ] [NAACL, 2022] [NewsEdits: A News Article Revision Dataset and a Novel Document-Level Reasoning Challenge](https://aclanthology.org/2022.naacl-main.10)
-- [ ] [NAACL, 2022] [DocTime: A Document-level Temporal Dependency Graph Parser](https://aclanthology.org/2022.naacl-main.73)
-- [ ] [NAACL, 2022] [Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.109)
-- [ ] [NAACL, 2022] [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://aclanthology.org/2022.naacl-main.111)
-- [ ] [NAACL, 2022] [SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.171)
-- [ ] [NAACL, 2022] [Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization](https://aclanthology.org/2022.naacl-main.199)
-- [ ] [NAACL, 2022] [Document-Level Relation Extraction with Sentences Importance Estimation and Focusing](https://aclanthology.org/2022.naacl-main.212)
-- [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
-- [ ] [NAACL, 2022] [DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction](https://aclanthology.org/2022.naacl-main.291)
-- [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
-- [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
-- [ ] [NAACL, 2022] [Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction](https://aclanthology.org/2022.naacl-main.395)
-- [ ] [NAACL, 2022] [Few-Shot Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.421)
-- [ ] [ACL, 2022] [Automatic Error Analysis for Document-level Information Extraction](https://aclanthology.org/2022.acl-long.274)
-- [ ] [ACL, 2022] [Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents](https://aclanthology.org/2022.acl-long.287)
-- [ ] [ACL, 2022] [Dynamic Global Memory for Document-level Argument Extraction](https://aclanthology.org/2022.acl-long.361)
-- [ ] [ACL, 2022] [Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution](https://aclanthology.org/2022.acl-short.88)
-- [ ] [FINDINGS, 2022] [Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion](https://aclanthology.org/2022.findings-acl.23)
-- [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
-- [ ] [FINDINGS, 2022] [Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation](https://aclanthology.org/2022.findings-acl.132)
-- [ ] [FINDINGS, 2022] [Rethinking Document-level Neural Machine Translation](https://aclanthology.org/2022.findings-acl.279)
-- [ ] [FINDINGS, 2021] [Exploring Sentence Community for Document-Level Event Extraction](https://aclanthology.org/2021.findings-emnlp.32)
-- [ ] [FINDINGS, 2021] [Bidirectional Hierarchical Attention Networks based on Document-level Context for Emotion Cause Extraction](https://aclanthology.org/2021.findings-emnlp.51)
-- [ ] [FINDINGS, 2021] [Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering](https://aclanthology.org/2021.findings-emnlp.89)
-- [ ] [FINDINGS, 2021] [ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://aclanthology.org/2021.findings-emnlp.164)
-- [ ] [EMNLP, 2021] [Learning Logic Rules for Document-Level Relation Extraction](https://aclanthology.org/2021.emnlp-main.95)
-- [ ] [EMNLP, 2021] [Coupling Context Modeling with Zero Pronoun Recovering for Document-Level Natural Language Generation](https://aclanthology.org/2021.emnlp-main.197)
-- [ ] [EMNLP, 2021] [Uncertain Local-to-Global Networks for Document-Level Event Factuality Identification](https://aclanthology.org/2021.emnlp-main.207)
-- [ ] [EMNLP, 2021] [Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation](https://aclanthology.org/2021.emnlp-main.262)
-- [ ] [EMNLP, 2021] [Document-level Entity-based Extraction as Template Generation](https://aclanthology.org/2021.emnlp-main.426)
-- [ ] [EMNLP, 2021] [Modular Self-Supervision for Document-Level Relation Extraction](https://aclanthology.org/2021.emnlp-main.429)
-- [ ] [EMNLP, 2021] [Modeling Document-Level Context for Event Detection via Important Context Selection](https://aclanthology.org/2021.emnlp-main.439)
-- [ ] [EMNLP, 2021] [Document-Level Text Simplification: Dataset, Criteria and Baseline](https://aclanthology.org/2021.emnlp-main.630)
-- [ ] [ACL, 2021] [G-Transformer for Document-Level Machine Translation](https://aclanthology.org/2021.acl-long.267)
-- [ ] [ACL, 2021] [Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker](https://aclanthology.org/2021.acl-long.274)
-- [ ] [ACL, 2021] [Document-level Event Extraction via Parallel Prediction Networks](https://aclanthology.org/2021.acl-long.492)
-- [ ] [ACL, 2021] [TIMERS: Document-level Temporal Relation Extraction](https://aclanthology.org/2021.acl-short.67)
-- [ ] [ACL, 2021] [Joint Detection and Coreference Resolution of Entities and Events with Document-level Context Aggregation](https://aclanthology.org/2021.acl-srw.18)
-- [ ] [FINDINGS, 2021] [SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction](https://aclanthology.org/2021.findings-acl.47)
-- [ ] [FINDINGS, 2021] [MRN: A Locally and Globally Mention-Based Reasoning Network for Document-Level Relation Extraction](https://aclanthology.org/2021.findings-acl.117)
-- [ ] [FINDINGS, 2021] [Discriminative Reasoning for Document-level Relation Extraction](https://aclanthology.org/2021.findings-acl.144)
-- [ ] [FINDINGS, 2021] [DocOIE: A Document-level Context-Aware Dataset for OpenIE](https://aclanthology.org/2021.findings-acl.210)
-- [ ] [FINDINGS, 2021] [A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction](https://aclanthology.org/2021.findings-acl.234)
-- [ ] [FINDINGS, 2021] [DocNLI: A Large-scale Dataset for Document-level Natural Language Inference](https://aclanthology.org/2021.findings-acl.435)
-- [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
-- [ ] [NAACL, 2021] [Why Do Document-Level Polarity Classifiers Fail?](https://aclanthology.org/2021.naacl-main.143)
-- [ ] [NAACL, 2021] [Graph Convolutional Networks for Event Causality Identification with Rich Document-level Structures](https://aclanthology.org/2021.naacl-main.273)
-- [ ] [NAACL, 2021] [Multi-Hop Transformer for Document-Level Machine Translation](https://aclanthology.org/2021.naacl-main.309)
-- [ ] [NAACL, 2021] [Context-aware Decoder for Neural Machine Translation using a Target-side Document-Level Language Model](https://aclanthology.org/2021.naacl-main.461)
-- [ ] [NAACL, 2021] [ActiveAnno: General-Purpose Document-Level Annotation Tool with Active Learning Integration](https://aclanthology.org/2021.naacl-demos.12)
-- [ ] [TACL, 2020] [Better Document-Level Machine Translation with Bayes’ Rule](https://aclanthology.org/2020.tacl-1.23)
-- [ ] [COLING, 2020] [Graph Enhanced Dual Attention Network for Document-Level Relation Extraction](https://aclanthology.org/2020.coling-main.136)
-- [ ] [COLING, 2020] [Document-level Relation Extraction with Dual-tier Heterogeneous Graph](https://aclanthology.org/2020.coling-main.143)
-- [ ] [COLING, 2020] [A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme Information](https://aclanthology.org/2020.coling-main.388)
-- [ ] [COLING, 2020] [Leveraging Discourse Rewards for Document-Level Neural Machine Translation](https://aclanthology.org/2020.coling-main.395)
-- [ ] [COLING, 2020] [Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction](https://aclanthology.org/2020.coling-main.461)
-- [ ] [COLING, 2020] [Improving Document-Level Sentiment Analysis with User and Product Context](https://aclanthology.org/2020.coling-main.590)
-- [ ] [EMNLP, 2020] [Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation](https://aclanthology.org/2020.emnlp-main.81)
-- [ ] [EMNLP, 2020] [Double Graph Based Reasoning for Document-level Relation Extraction](https://aclanthology.org/2020.emnlp-main.127)
-- [ ] [EMNLP, 2020] [Dynamic Context Selection for Document-level Neural Machine Translation via Reinforcement Learning](https://aclanthology.org/2020.emnlp-main.175)
-- [ ] [EMNLP, 2020] [Denoising Relation Extraction from Document-level Distant Supervision](https://aclanthology.org/2020.emnlp-main.300)
-- [ ] [EMNLP, 2020] [Global-to-Local Neural Networks for Document-Level Relation Extraction](https://aclanthology.org/2020.emnlp-main.303)
-- [ ] [EMNLP, 2020] [Substance over Style: Document-Level Targeted Content Transfer](https://aclanthology.org/2020.emnlp-main.526)
-- [ ] [EMNLP, 2020] [Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification](https://aclanthology.org/2020.emnlp-main.570)
-- [ ] [FINDINGS, 2020] [The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction](https://aclanthology.org/2020.findings-emnlp.409)
-- [ ] [ACL, 2020] [Reasoning with Latent Structure Refinement for Document-Level Relation Extraction](https://aclanthology.org/2020.acl-main.141)
-- [ ] [ACL, 2020] [SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://aclanthology.org/2020.acl-main.207)
-- [ ] [ACL, 2020] [A Simple and Effective Unified Encoder for Document-Level Machine Translation](https://aclanthology.org/2020.acl-main.321)
-- [ ] [ACL, 2020] [Aspect Sentiment Classification with Document-level Sentiment Preference Modeling](https://aclanthology.org/2020.acl-main.338)
-- [ ] [ACL, 2020] [Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering](https://aclanthology.org/2020.acl-main.501)
-- [ ] [ACL, 2020] [SciREX: A Challenge Dataset for Document-Level Information Extraction](https://aclanthology.org/2020.acl-main.670)
-- [ ] [ACL, 2020] [Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding](https://aclanthology.org/2020.acl-main.714)
-- [ ] [EMNLP, 2019] [Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction](https://aclanthology.org/D19-1032)
-- [ ] [EMNLP, 2019] [Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level Translation](https://aclanthology.org/D19-1164)
-- [ ] [EMNLP, 2019] [Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation](https://aclanthology.org/D19-1168)
-- [ ] [EMNLP, 2019] [Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://aclanthology.org/D19-1498)
-- [ ] [EMNLP, 2019] [Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning](https://aclanthology.org/D19-1560)
-- [ ] [ACL, 2019] [DocRED: A Large-Scale Document-Level Relation Extraction Dataset](https://aclanthology.org/P19-1074)
-- [ ] [ACL, 2019] [Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://aclanthology.org/P19-1423)
-- [ ] [NAACL, 2019] [Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation](https://aclanthology.org/N19-1033)
-- [ ] [NAACL, 2019] [A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification](https://aclanthology.org/N19-1036)
-- [ ] [NAACL, 2019] [Word-Node2Vec: Improving Word Embedding with Document-Level Non-Local Word Co-occurrences](https://aclanthology.org/N19-1109)
-- [ ] [NAACL, 2019] [Modeling Document-level Causal Structures for Event Causal Relation Identification](https://aclanthology.org/N19-1179)
-- [ ] [NAACL, 2019] [Document-Level Event Factuality Identification via Adversarial Neural Network](https://aclanthology.org/N19-1287)
-- [ ] [NAACL, 2019] [Document-Level N-ary Relation Extraction with Multiscale Representation Learning](https://aclanthology.org/N19-1370)
-- [ ] [EMNLP, 2018] [Improving the Transformer Translation Model with Document-Level Context](https://aclanthology.org/D18-1049)
-- [ ] [EMNLP, 2018] [Document-Level Neural Machine Translation with Hierarchical Attention Networks](https://aclanthology.org/D18-1325)
-- [ ] [EMNLP, 2018] [Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation](https://aclanthology.org/D18-1512)
-- [ ] [COLING, 2018] [Document-level Multi-aspect Sentiment Classification by Jointly Modeling Users, Aspects, and Overall Ratings](https://aclanthology.org/C18-1079)
-- [ ] [ACL, 2018] [DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data](https://aclanthology.org/P18-4009)
-- [ ] [EMNLP, 2017] [Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension](https://aclanthology.org/D17-1217)
-- [ ] [EMNLP, 2016] [Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification](https://aclanthology.org/D16-1172)
-- [ ] [ACL, 2016] [Document-level Sentiment Inference with Social, Faction, and Discourse Context](https://aclanthology.org/P16-1032)
-- [ ] [EMNLP, 2015] [Better Document-level Sentiment Analysis from RST Discourse Parsing](https://aclanthology.org/D15-1263)
-- [ ] [NAACL, 2015] [Discourse and Document-level Information for Evaluating Language Output Tasks](https://aclanthology.org/N15-2016)
-- [ ] [ACL, 2014] [Effective Document-Level Features for Chinese Patent Word Segmentation](https://aclanthology.org/P14-2033)
-- [ ] [EMNLP, 2013] [Lexical Chain Based Cohesion Models for Document-Level Statistical Machine Translation](https://aclanthology.org/D13-1163)
-- [ ] [ACL, 2013] [Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis](https://aclanthology.org/P13-1048)
-- [ ] [ACL, 2013] [Bilingual Lexical Cohesion Trigger Model for Document-Level Machine Translation](https://aclanthology.org/P13-2068)
-- [ ] [ACL, 2013] [Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation](https://aclanthology.org/P13-4033)
-- [ ] [ACL, 2012] [Identifying High-Impact Sub-Structures for Convolution Kernels in Document-level Sentiment Classification](https://aclanthology.org/P12-2066)
-- [ ] [EMNLP, 2011] [Learning Local Content Shift Detectors from Document-level Information](https://aclanthology.org/D11-1070)
-- [ ] [EMNLP, 2011] [Cache-based Document-level Statistical Machine Translation](https://aclanthology.org/D11-1084)
-- [ ] [ACL, 2011] [Reordering Constraint Based on Document-Level Context](https://aclanthology.org/P11-2076)
-- [ ] [EMNLP, 2010] [Multi-Level Structured Models for Document-Level Sentiment Classification](https://aclanthology.org/D10-1102)
-- [ ] [ACL, 2008] [Learning Document-Level Semantic Properties from Free-Text Annotations](https://aclanthology.org/P08-1031)

results/ee-paper-list.md

@@ -1,396 +0,0 @@
-- [ ] [COLING, 2022] [Different Data, Different Modalities! Reinforced Data Splitting for Effective Multimodal Information Extraction from Social Media Posts](https://aclanthology.org/2022.coling-1.160)
-- [ ] [COLING, 2022] [KiPT: Knowledge-injected Prompt Tuning for Event Detection](https://aclanthology.org/2022.coling-1.169)
-- [ ] [COLING, 2022] [OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction](https://aclanthology.org/2022.coling-1.170)
-- [ ] [COLING, 2022] [Event Detection with Dual Relational Graph Attention Networks](https://aclanthology.org/2022.coling-1.172)
-- [ ] [COLING, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](https://aclanthology.org/2022.coling-1.173)
-- [ ] [COLING, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](https://aclanthology.org/2022.coling-1.173)
-- [ ] [COLING, 2022] [Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection](https://aclanthology.org/2022.coling-1.189)
-- [ ] [COLING, 2022] [Event Causality Extraction with Event Argument Correlations](https://aclanthology.org/2022.coling-1.201)
-- [ ] [COLING, 2022] [Event Causality Extraction with Event Argument Correlations](https://aclanthology.org/2022.coling-1.201)
-- [ ] [COLING, 2022] [DESED: Dialogue-based Explanation for Sentence-level Event Detection](https://aclanthology.org/2022.coling-1.219)
-- [ ] [COLING, 2022] [CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction](https://aclanthology.org/2022.coling-1.221)
-- [ ] [COLING, 2022] [Unregulated Chinese-to-English Data Expansion Does NOT Work for Neural Event Detection](https://aclanthology.org/2022.coling-1.232)
-- [ ] [COLING, 2022] [Text-to-Text Extraction and Verbalization of Biomedical Event Graphs](https://aclanthology.org/2022.coling-1.238)
-- [ ] [COLING, 2022] [Event Extraction in Video Transcripts](https://aclanthology.org/2022.coling-1.625)
-- [ ] [FINDINGS, 2022] [Event Detection for Suicide Understanding](https://aclanthology.org/2022.findings-naacl.150)
-- [ ] [FINDINGS, 2022] [Zero-Shot Event Detection Based on Ordered Contrastive Learning and Prompt-Based Prediction](https://aclanthology.org/2022.findings-naacl.196)
-- [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
-- [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
-- [ ] [NAACL, 2022] [Cross-document Misinformation Detection based on Event Graph Reasoning](https://aclanthology.org/2022.naacl-main.40)
-- [ ] [NAACL, 2022] [CompactIE: Compact Facts in Open Information Extraction](https://aclanthology.org/2022.naacl-main.65)
-- [ ] [NAACL, 2022] [DEGREE: A Data-Efficient Generation-Based Event Extraction Model](https://aclanthology.org/2022.naacl-main.138)
-- [ ] [NAACL, 2022] [MINION: a Large-Scale and Diverse Dataset for Multilingual Event Detection](https://aclanthology.org/2022.naacl-main.166)
-- [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
-- [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
-- [ ] [NAACL, 2022] [GMN: Generative Multi-modal Network for Practical Document Information Extraction](https://aclanthology.org/2022.naacl-main.276)
-- [ ] [NAACL, 2022] [DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction](https://aclanthology.org/2022.naacl-main.291)
-- [ ] [NAACL, 2022] [GenIE: Generative Information Extraction](https://aclanthology.org/2022.naacl-main.342)
-- [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
-- [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
-- [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
-- [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
-- [ ] [NAACL, 2022] [Cross-Lingual Event Detection via Optimized Adversarial Training](https://aclanthology.org/2022.naacl-main.409)
-- [ ] [NAACL, 2022] [ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations](https://aclanthology.org/2022.naacl-demo.4)
-- [ ] [NAACL, 2022] [A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction](https://aclanthology.org/2022.naacl-demo.8)
-- [ ] [NAACL, 2022] [FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction](https://aclanthology.org/2022.naacl-demo.14)
-- [ ] [NAACL, 2022] [New Frontiers of Information Extraction](https://aclanthology.org/2022.naacl-tutorials.3)
-- [ ] [ACL, 2022] [Legal Judgment Prediction via Event Extraction with Constraints](https://aclanthology.org/2022.acl-long.48)
-- [ ] [ACL, 2022] [Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction](https://aclanthology.org/2022.acl-long.179)
-- [ ] [ACL, 2022] [Text-to-Table: A New Way of Information Extraction](https://aclanthology.org/2022.acl-long.180)
-- [ ] [ACL, 2022] [FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction](https://aclanthology.org/2022.acl-long.260)
-- [ ] [ACL, 2022] [Automatic Error Analysis for Document-level Information Extraction](https://aclanthology.org/2022.acl-long.274)
-- [ ] [ACL, 2022] [BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation](https://aclanthology.org/2022.acl-long.307)
-- [ ] [ACL, 2022] [Saliency as Evidence: Event Detection with Trigger Saliency Attribution](https://aclanthology.org/2022.acl-long.313)
-- [ ] [ACL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](https://aclanthology.org/2022.acl-long.317)
-- [ ] [ACL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](https://aclanthology.org/2022.acl-long.317)
-- [ ] [ACL, 2022] [Dynamic Prefix-Tuning for Generative Template-based Event Extraction](https://aclanthology.org/2022.acl-long.358)
-- [ ] [ACL, 2022] [Unified Structure Generation for Universal Information Extraction](https://aclanthology.org/2022.acl-long.395)
-- [ ] [ACL, 2022] [OIE@OIA: an Adaptable and Efficient Open Information Extraction Framework](https://aclanthology.org/2022.acl-long.430)
-- [ ] [ACL, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](https://aclanthology.org/2022.acl-long.466)
-- [ ] [ACL, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](https://aclanthology.org/2022.acl-long.466)
-- [ ] [ACL, 2022] [MILIE: Modular & Iterative Multilingual Open Information Extraction](https://aclanthology.org/2022.acl-long.478)
-- [ ] [ACL, 2022] [AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark](https://aclanthology.org/2022.acl-demo.5)
-- [ ] [FINDINGS, 2022] [Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding](https://aclanthology.org/2022.findings-acl.16)
-- [ ] [FINDINGS, 2022] [LEVEN: A Large-Scale Chinese Legal Event Detection Dataset](https://aclanthology.org/2022.findings-acl.17)
-- [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
-- [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
-- [ ] [FINDINGS, 2021] [Joint Multimedia Event Extraction from Video and Article](https://aclanthology.org/2021.findings-emnlp.8)
-- [ ] [FINDINGS, 2021] [Self-Attention Graph Residual Convolutional Networks for Event Detection with dependency relations](https://aclanthology.org/2021.findings-emnlp.28)
-- [ ] [FINDINGS, 2021] [Exploring Sentence Community for Document-Level Event Extraction](https://aclanthology.org/2021.findings-emnlp.32)
-- [ ] [EMNLP, 2021] [Zero-Shot Information Extraction as a Unified Text-to-Triple Translation](https://aclanthology.org/2021.emnlp-main.94)
-- [ ] [EMNLP, 2021] [Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction](https://aclanthology.org/2021.emnlp-main.149)
-- [ ] [EMNLP, 2021] [Treasures Outside Contexts: Improving Event Detection via Global Statistics](https://aclanthology.org/2021.emnlp-main.206)
-- [ ] [EMNLP, 2021] [Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction](https://aclanthology.org/2021.emnlp-main.214)
-- [ ] [EMNLP, 2021] [Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction](https://aclanthology.org/2021.emnlp-main.214)
-- [ ] [EMNLP, 2021] [Cost-effective End-to-end Information Extraction for Semi-structured Document Images](https://aclanthology.org/2021.emnlp-main.271)
-- [ ] [EMNLP, 2021] [Learning Prototype Representations Across Few-Shot Tasks for Event Detection](https://aclanthology.org/2021.emnlp-main.427)
-- [ ] [EMNLP, 2021] [Lifelong Event Detection with Knowledge Transfer](https://aclanthology.org/2021.emnlp-main.428)
-- [ ] [EMNLP, 2021] [Learning from Noisy Labels for Entity-Centric Information Extraction](https://aclanthology.org/2021.emnlp-main.437)
-- [ ] [EMNLP, 2021] [Modeling Document-Level Context for Event Detection via Important Context Selection](https://aclanthology.org/2021.emnlp-main.439)
-- [ ] [EMNLP, 2021] [Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments](https://aclanthology.org/2021.emnlp-main.440)
-- [ ] [EMNLP, 2021] [Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments](https://aclanthology.org/2021.emnlp-main.440)
-- [ ] [EMNLP, 2021] [Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention](https://aclanthology.org/2021.emnlp-main.637)
-- [ ] [EMNLP, 2021] [Uncovering Main Causalities for Long-tailed Information Extraction](https://aclanthology.org/2021.emnlp-main.763)
-- [ ] [EMNLP, 2021] [Maximal Clique Based Non-Autoregressive Open Information Extraction](https://aclanthology.org/2021.emnlp-main.764)
-- [ ] [EMNLP, 2021] [Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction](https://aclanthology.org/2021.emnlp-main.815)
-- [ ] [EMNLP, 2021] [Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction](https://aclanthology.org/2021.emnlp-main.815)
-- [ ] [ACL, 2021] [CitationIE: Leveraging the Citation Graph for Scientific Information Extraction](https://aclanthology.org/2021.acl-long.59)
-- [ ] [ACL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](https://aclanthology.org/2021.acl-long.60)
-- [ ] [ACL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](https://aclanthology.org/2021.acl-long.60)
-- [ ] [ACL, 2021] [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://aclanthology.org/2021.acl-long.217)
-- [ ] [ACL, 2021] [OntoED: Low-resource Event Detection with Ontology Embedding](https://aclanthology.org/2021.acl-long.220)
-- [ ] [ACL, 2021] [Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker](https://aclanthology.org/2021.acl-long.274)
-- [ ] [ACL, 2021] [Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction](https://aclanthology.org/2021.acl-long.360)
-- [ ] [ACL, 2021] [Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction](https://aclanthology.org/2021.acl-long.360)
-- [ ] [ACL, 2021] [CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction](https://aclanthology.org/2021.acl-long.363)
-- [ ] [ACL, 2021] [MLBiNet: A Cross-Sentence Collective Event Detection Network](https://aclanthology.org/2021.acl-long.373)
-- [ ] [ACL, 2021] [Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation](https://aclanthology.org/2021.acl-long.489)
-- [ ] [ACL, 2021] [Unleash GPT-2 Power for Event Detection](https://aclanthology.org/2021.acl-long.490)
-- [ ] [ACL, 2021] [CLEVE: Contrastive Pre-training for Event Extraction](https://aclanthology.org/2021.acl-long.491)
-- [ ] [ACL, 2021] [Document-level Event Extraction via Parallel Prediction Networks](https://aclanthology.org/2021.acl-long.492)
-- [ ] [ACL, 2021] [ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction](https://aclanthology.org/2021.acl-short.41)
-- [ ] [ACL, 2021] [Zero-shot Event Extraction via Transfer Learning: Challenges and Insights](https://aclanthology.org/2021.acl-short.42)
-- [ ] [ACL, 2021] [CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet](https://aclanthology.org/2021.acl-demo.11)
-- [ ] [FINDINGS, 2021] [Few-Shot Event Detection with Prototypical Amortized Conditional Random Field](https://aclanthology.org/2021.findings-acl.3)
-- [ ] [FINDINGS, 2021] [CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction](https://aclanthology.org/2021.findings-acl.14)
-- [ ] [FINDINGS, 2021] [Spatial Dependency Parsing for Semi-Structured Document Information Extraction](https://aclanthology.org/2021.findings-acl.28)
-- [ ] [FINDINGS, 2021] [A Dialogue-based Information Extraction System for Medical Insurance Assessment](https://aclanthology.org/2021.findings-acl.58)
-- [ ] [FINDINGS, 2021] [Zero-shot Label-Aware Event Trigger and Argument Classification](https://aclanthology.org/2021.findings-acl.114)
-- [ ] [FINDINGS, 2021] [Event Detection as Graph Parsing](https://aclanthology.org/2021.findings-acl.142)
-- [ ] [FINDINGS, 2021] [Event Extraction from Historical Texts: A New Dataset for Black Rebellions](https://aclanthology.org/2021.findings-acl.211)
-- [ ] [FINDINGS, 2021] [Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection](https://aclanthology.org/2021.findings-acl.214)
-- [ ] [FINDINGS, 2021] [GrantRel: Grant Information Extraction via Joint Entity and Relation Extraction](https://aclanthology.org/2021.findings-acl.236)
-- [ ] [FINDINGS, 2021] [Unsupervised Domain Adaptation for Event Detection using Domain-specific Adapters](https://aclanthology.org/2021.findings-acl.351)
-- [ ] [FINDINGS, 2021] [Revisiting the Evaluation of End-to-end Event Extraction](https://aclanthology.org/2021.findings-acl.405)
-- [ ] [NAACL, 2021] [Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks](https://aclanthology.org/2021.naacl-main.3)
-- [ ] [NAACL, 2021] [Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction](https://aclanthology.org/2021.naacl-main.4)
-- [ ] [NAACL, 2021] [Event Time Extraction and Propagation via Graph Attention Networks](https://aclanthology.org/2021.naacl-main.6)
-- [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
-- [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
-- [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
-- [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
-- [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
-- [ ] [COLING, 2020] [Hierarchical Chinese Legal event extraction via Pedal Attention Mechanism](https://aclanthology.org/2020.coling-main.9)
-- [ ] [COLING, 2020] [Is Killed More Significant than Fled? A Contextual Model for Salient Event Detection](https://aclanthology.org/2020.coling-main.10)
-- [ ] [COLING, 2020] [KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision](https://aclanthology.org/2020.coling-main.135)
-- [ ] [COLING, 2020] [Joint Event Extraction with Hierarchical Policy Network](https://aclanthology.org/2020.coling-main.239)
-- [ ] [EMNLP, 2020] [Event Extraction by Answering (Almost) Natural Questions](https://aclanthology.org/2020.emnlp-main.49)
-- [ ] [EMNLP, 2020] [Incremental Event Detection via Knowledge Consolidation Networks](https://aclanthology.org/2020.emnlp-main.52)
-- [ ] [EMNLP, 2020] [Semi-supervised New Event Type Induction and Event Detection](https://aclanthology.org/2020.emnlp-main.53)
-- [ ] [EMNLP, 2020] [Event Extraction as Machine Reading Comprehension](https://aclanthology.org/2020.emnlp-main.128)
-- [ ] [EMNLP, 2020] [MAVEN: A Massive General Domain Event Detection Dataset](https://aclanthology.org/2020.emnlp-main.129)
-- [ ] [EMNLP, 2020] [OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction](https://aclanthology.org/2020.emnlp-main.306)
-- [ ] [EMNLP, 2020] [An Empirical Study of Pre-trained Transformers for Arabic Information Extraction](https://aclanthology.org/2020.emnlp-main.382)
-- [ ] [EMNLP, 2020] [Biomedical Event Extraction as Sequence Labeling](https://aclanthology.org/2020.emnlp-main.431)
-- [ ] [EMNLP, 2020] [Introducing a New Dataset for Event Detection in Cybersecurity Texts](https://aclanthology.org/2020.emnlp-main.433)
-- [ ] [EMNLP, 2020] [Affective Event Classification with Discourse-enhanced Self-training](https://aclanthology.org/2020.emnlp-main.452)
-- [ ] [EMNLP, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](https://aclanthology.org/2020.emnlp-main.461)
-- [ ] [EMNLP, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](https://aclanthology.org/2020.emnlp-main.461)
-- [ ] [EMNLP, 2020] [Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction](https://aclanthology.org/2020.emnlp-main.690)
-- [ ] [FINDINGS, 2020] [Syntactic and Semantic-driven Learning for Open Information Extraction](https://aclanthology.org/2020.findings-emnlp.69)
-- [ ] [FINDINGS, 2020] [Event Extraction as Multi-turn Question Answering](https://aclanthology.org/2020.findings-emnlp.73)
-- [ ] [FINDINGS, 2020] [Multiˆ2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT](https://aclanthology.org/2020.findings-emnlp.99)
-- [ ] [FINDINGS, 2020] [Biomedical Event Extraction with Hierarchical Knowledge Graphs](https://aclanthology.org/2020.findings-emnlp.114)
-- [ ] [FINDINGS, 2020] [Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning](https://aclanthology.org/2020.findings-emnlp.121)
-- [ ] [FINDINGS, 2020] [Edge-Enhanced Graph Convolution Networks for Event Detection with Syntactic Relation](https://aclanthology.org/2020.findings-emnlp.211)
-- [ ] [FINDINGS, 2020] [How Does Context Matter? On the Robustness of Event Detection with Context-Selective Mask Generalization](https://aclanthology.org/2020.findings-emnlp.229)
-- [ ] [FINDINGS, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.318)
-- [ ] [FINDINGS, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.318)
-- [ ] [FINDINGS, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.326)
-- [ ] [FINDINGS, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.326)
-- [ ] [ACL, 2020] [The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain](https://aclanthology.org/2020.acl-main.116)
-- [ ] [ACL, 2020] [Cross-media Structured Common Space for Multimedia Event Extraction](https://aclanthology.org/2020.acl-main.230)
-- [ ] [ACL, 2020] [IMoJIE: Iterative Memory-Based Joint Open Information Extraction](https://aclanthology.org/2020.acl-main.521)
-- [ ] [ACL, 2020] [Improving Event Detection via Open-domain Trigger Knowledge](https://aclanthology.org/2020.acl-main.522)
-- [ ] [ACL, 2020] [Representation Learning for Information Extraction from Form-like Documents](https://aclanthology.org/2020.acl-main.580)
-- [ ] [ACL, 2020] [A Two-Step Approach for Implicit Event Argument Detection](https://aclanthology.org/2020.acl-main.667)
-- [ ] [ACL, 2020] [SciREX: A Challenge Dataset for Document-Level Information Extraction](https://aclanthology.org/2020.acl-main.670)
-- [ ] [ACL, 2020] [A Joint Neural Model for Information Extraction with Global Features](https://aclanthology.org/2020.acl-main.713)
-- [ ] [ACL, 2020] [Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding](https://aclanthology.org/2020.acl-main.714)
-- [ ] [ACL, 2020] [Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web](https://aclanthology.org/2020.acl-tutorials.6)
-- [ ] [EMNLP, 2019] [Open Event Extraction from Online Text using a Generative Adversarial Network](https://aclanthology.org/D19-1027)
-- [ ] [EMNLP, 2019] [Cross-lingual Structure Transfer for Relation and Event Extraction](https://aclanthology.org/D19-1030)
-- [ ] [EMNLP, 2019] [Cross-lingual Structure Transfer for Relation and Event Extraction](https://aclanthology.org/D19-1030)
-- [ ] [EMNLP, 2019] [Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction](https://aclanthology.org/D19-1032)
-- [ ] [EMNLP, 2019] [Event Detection with Trigger-Aware Lattice Neural Network](https://aclanthology.org/D19-1033)
-- [ ] [EMNLP, 2019] [Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction](https://aclanthology.org/D19-1041)
-- [ ] [EMNLP, 2019] [Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction](https://aclanthology.org/D19-1041)
-- [ ] [EMNLP, 2019] [Supervising Unsupervised Open Information Extraction Models](https://aclanthology.org/D19-1067)
-- [ ] [EMNLP, 2019] [Neural Cross-Lingual Event Detection with Minimal Parallel Resources](https://aclanthology.org/D19-1068)
-- [ ] [EMNLP, 2019] [A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection](https://aclanthology.org/D19-1381)
-- [ ] [EMNLP, 2019] [Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes](https://aclanthology.org/D19-1580)
-- [ ] [EMNLP, 2019] [Event Detection with Multi-Order Graph Convolution and Aggregated Attention](https://aclanthology.org/D19-1582)
-- [ ] [EMNLP, 2019] [Coverage of Information Extraction from Sentences and Paragraphs](https://aclanthology.org/D19-1583)
-- [ ] [EMNLP, 2019] [HMEAE: Hierarchical Modular Event Argument Extraction](https://aclanthology.org/D19-1584)
-- [ ] [EMNLP, 2019] [HMEAE: Hierarchical Modular Event Argument Extraction](https://aclanthology.org/D19-1584)
-- [ ] [EMNLP, 2019] [Entity, Relation, and Event Extraction with Contextualized Span Representations](https://aclanthology.org/D19-1585)
-- [ ] [ACL, 2019] [Unsupervised Information Extraction: Regularizing Discriminative Approaches with Relation Distribution Losses](https://aclanthology.org/P19-1133)
-- [ ] [ACL, 2019] [Open Domain Event Extraction Using Neural Latent Variable Models](https://aclanthology.org/P19-1276)
-- [ ] [ACL, 2019] [Literary Event Detection](https://aclanthology.org/P19-1353)
-- [ ] [ACL, 2019] [Distilling Discrimination and Generalization Knowledge for Event Detection via Delta-Representation Learning](https://aclanthology.org/P19-1429)
-- [ ] [ACL, 2019] [Cost-sensitive Regularization for Label Confusion-aware Event Detection](https://aclanthology.org/P19-1521)
-- [ ] [ACL, 2019] [Exploring Pre-trained Language Models for Event Extraction and Generation](https://aclanthology.org/P19-1522)
-- [ ] [ACL, 2019] [Improving Open Information Extraction via Iterative Rank-Aware Learning](https://aclanthology.org/P19-1523)
-- [ ] [ACL, 2019] [Rapid Customization for Event Extraction](https://aclanthology.org/P19-3006)
-- [ ] [NAACL, 2019] [Event Detection without Triggers](https://aclanthology.org/N19-1080)
-- [ ] [NAACL, 2019] [GraphIE: A Graph-Based Framework for Information Extraction](https://aclanthology.org/N19-1082)
-- [ ] [NAACL, 2019] [OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference](https://aclanthology.org/N19-1083)
-- [ ] [NAACL, 2019] [Adversarial Training for Weakly Supervised Event Detection](https://aclanthology.org/N19-1105)
-- [ ] [NAACL, 2019] [Biomedical Event Extraction based on Knowledge-driven Tree-LSTM](https://aclanthology.org/N19-1145)
-- [ ] [NAACL, 2019] [Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction](https://aclanthology.org/N19-1150)
-- [ ] [NAACL, 2019] [Open Information Extraction from Question-Answer Pairs](https://aclanthology.org/N19-1239)
-- [ ] [NAACL, 2019] [A general framework for information extraction using dynamic span graphs](https://aclanthology.org/N19-1308)
-- [ ] [NAACL, 2019] [OpenCeres: When Open Information Extraction Meets the Semi-Structured Web](https://aclanthology.org/N19-1309)
-- [ ] [NAACL, 2019] [Graph Convolution for Multimodal Information Extraction from Visually Rich Documents](https://aclanthology.org/N19-2005)
-- [ ] [NAACL, 2019] [TOI-CNN: a Solution of Information Extraction on Chinese Insurance Policy](https://aclanthology.org/N19-2022)
-- [ ] [NAACL, 2019] [SEDTWik: Segmentation-based Event Detection from Tweets Using Wikipedia](https://aclanthology.org/N19-3011)
-- [ ] [NAACL, 2019] [Multilingual Entity, Relation, Event and Human Value Extraction](https://aclanthology.org/N19-4019)
-- [ ] [NAACL, 2019] [Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence](https://aclanthology.org/W19-2606)
-- [ ] [CL, 2019] [Novel Event Detection and Classification for Historical Texts](https://aclanthology.org/J19-2002)
-- [ ] [CL, 2019] [Novel Event Detection and Classification for Historical Texts](https://aclanthology.org/J19-2002)
-- [ ] [TACL, 2018] [Event Time Extraction with a Decision Tree of Neural Classifiers](https://aclanthology.org/Q18-1006)
-- [ ] [EMNLP, 2018] [Event Detection with Neural Networks: A Rigorous Empirical Evaluation](https://aclanthology.org/D18-1122)
-- [ ] [EMNLP, 2018] [Exploiting Contextual Information via Dynamic Memory Network for Event Detection](https://aclanthology.org/D18-1127)
-- [ ] [EMNLP, 2018] [Temporal Information Extraction by Predicting Relative Time-lines](https://aclanthology.org/D18-1155)
-- [ ] [EMNLP, 2018] [Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms](https://aclanthology.org/D18-1158)
-- [ ] [EMNLP, 2018] [Visual Supervision in Bootstrapped Information Extraction](https://aclanthology.org/D18-1229)
-- [ ] [EMNLP, 2018] [Similar but not the Same: Word Sense Disambiguation Improves Event Detection via Neural Representation Matching](https://aclanthology.org/D18-1517)
-- [ ] [CL, 2018] [Last Words: What Can Be Accomplished with the State of the Art in Information Extraction? A Personal View](https://aclanthology.org/J18-4004)
-- [ ] [EMNLP, 2018] [A Multilingual Information Extraction Pipeline for Investigative Journalism](https://aclanthology.org/D18-2014)
-- [ ] [EMNLP, 2018] [Joint Modeling for Query Expansion and Information Extraction with Reinforcement Learning](https://aclanthology.org/W18-5506)
-- [ ] [COLING, 2018] [Low-resource Cross-lingual Event Type Detection via Distant Supervision with Minimal Effort](https://aclanthology.org/C18-1007)
-- [ ] [COLING, 2018] [Open-Domain Event Detection using Distant Supervision](https://aclanthology.org/C18-1075)
-- [ ] [COLING, 2018] [Open Information Extraction from Conjunctive Sentences](https://aclanthology.org/C18-1194)
-- [ ] [COLING, 2018] [Graphene: Semantically-Linked Propositions in Open Information Extraction](https://aclanthology.org/C18-1195)
-- [ ] [COLING, 2018] [Open Information Extraction on Scientific Text: An Evaluation](https://aclanthology.org/C18-1289)
-- [ ] [COLING, 2018] [A Survey on Open Information Extraction](https://aclanthology.org/C18-1326)
-- [ ] [COLING, 2018] [Graphene: a Context-Preserving Open Information Extraction System](https://aclanthology.org/C18-2021)
-- [ ] [ACL, 2018] [Self-regulation: Employing a Generative Adversarial Network to Improve Event Detection](https://aclanthology.org/P18-1048)
-- [ ] [ACL, 2018] [Context-Aware Neural Model for Temporal Information Extraction](https://aclanthology.org/P18-1049)
-- [ ] [ACL, 2018] [Adaptive Scaling for Sparse Detection in Information Extraction](https://aclanthology.org/P18-1095)
-- [ ] [ACL, 2018] [Nugget Proposal Networks for Chinese Event Detection](https://aclanthology.org/P18-1145)
-- [ ] [ACL, 2018] [Zero-Shot Transfer Learning for Event Extraction](https://aclanthology.org/P18-1201)
-- [ ] [ACL, 2018] [Neural Open Information Extraction](https://aclanthology.org/P18-2065)
-- [ ] [ACL, 2018] [Document Embedding Enhanced Event Detection with Hierarchical and Supervised Attention](https://aclanthology.org/P18-2066)
-- [ ] [ACL, 2018] [DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data](https://aclanthology.org/P18-4009)
-- [ ] [ACL, 2018] [Economic Event Detection in Company-Specific News Text](https://aclanthology.org/W18-3101)
-- [ ] [NAACL, 2018] [Supervised Open Information Extraction](https://aclanthology.org/N18-1081)
-- [ ] [NAACL, 2018] [Keep Your Bearings: Lightly-Supervised Information Extraction with Ladder Networks That Avoids Semantic Drift](https://aclanthology.org/N18-2057)
-- [ ] [NAACL, 2018] [Semi-Supervised Event Extraction with Paraphrase Clusters](https://aclanthology.org/N18-2058)
-- [ ] [NAACL, 2018] [Syntactic Patterns Improve Information Extraction for Medical Search](https://aclanthology.org/N18-2060)
-- [ ] [EMNLP, 2017] [Temporal Information Extraction for Question Answering Using Syntactic Dependencies in an LSTM-based Architecture](https://aclanthology.org/D17-1092)
-- [ ] [EMNLP, 2017] [MinIE: Minimizing Facts in Open Information Extraction](https://aclanthology.org/D17-1278)
-- [ ] [EMNLP, 2017] [Scientific Information Extraction with Semi-supervised Neural Tagging](https://aclanthology.org/D17-1279)
-- [ ] [EMNLP, 2017] [Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods](https://aclanthology.org/D17-1281)
-- [ ] [ACL, 2017] [Automatically Labeled Data Generation for Large Scale Event Extraction](https://aclanthology.org/P17-1038)
-- [ ] [ACL, 2017] [Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms](https://aclanthology.org/P17-1164)
-- [ ] [ACL, 2017] [English Event Detection With Translated Language Features](https://aclanthology.org/P17-2046)
-- [ ] [ACL, 2017] [Answering Complex Questions Using Open Information Extraction](https://aclanthology.org/P17-2049)
-- [ ] [COLING, 2016] [Leveraging Multilingual Training for Limited Resource Event Extraction](https://aclanthology.org/C16-1114)
-- [ ] [COLING, 2016] [Incremental Global Event Extraction](https://aclanthology.org/C16-1215)
-- [ ] [COLING, 2016] [Event Detection with Burst Information Networks](https://aclanthology.org/C16-1309)
-- [ ] [COLING, 2016] [Video Event Detection by Exploiting Word Dependencies from Image Captions](https://aclanthology.org/C16-1313)
-- [ ] [COLING, 2016] [OCR++: A Robust Framework For Information Extraction from Scholarly Articles](https://aclanthology.org/C16-1320)
-- [ ] [COLING, 2016] [Multilingual Information Extraction with PolyglotIE](https://aclanthology.org/C16-2056)
-- [ ] [EMNLP, 2016] [Nested Propositions in Open Information Extraction](https://aclanthology.org/D16-1006)
-- [ ] [EMNLP, 2016] [Event Detection and Co-reference with Minimal Supervision](https://aclanthology.org/D16-1038)
-- [ ] [EMNLP, 2016] [Modeling Skip-Grams for Event Detection with Convolutional Neural Networks](https://aclanthology.org/D16-1085)
-- [ ] [EMNLP, 2016] [Porting an Open Information Extraction System from English to German](https://aclanthology.org/D16-1086)
-- [ ] [EMNLP, 2016] [Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities](https://aclanthology.org/D16-1152)
-- [ ] [EMNLP, 2016] [Creating a Large Benchmark for Open Information Extraction](https://aclanthology.org/D16-1252)
-- [ ] [EMNLP, 2016] [Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning](https://aclanthology.org/D16-1261)
-- [ ] [ACL, 2016] [Liberal Event Extraction and Event Schema Induction](https://aclanthology.org/P16-1025)
-- [ ] [ACL, 2016] [Jointly Event Extraction and Visualization on Twitter via Probabilistic Modelling](https://aclanthology.org/P16-1026)
-- [ ] [ACL, 2016] [RBPB: Regularization-Based Pattern Balancing Method for Event Extraction](https://aclanthology.org/P16-1116)
-- [ ] [ACL, 2016] [Leveraging FrameNet to Improve Automatic Event Detection](https://aclanthology.org/P16-1201)
-- [ ] [ACL, 2016] [A Language-Independent Neural Network for Event Detection](https://aclanthology.org/P16-2011)
-- [ ] [ACL, 2016] [Event Nugget Detection with Forward-Backward Recurrent Neural Networks](https://aclanthology.org/P16-2060)
-- [ ] [ACL, 2016] [new/s/leak – Information Extraction and Visualization for Investigative Data Journalists](https://aclanthology.org/P16-4028)
-- [ ] [NAACL, 2016] [Joint Event Extraction via Recurrent Neural Networks](https://aclanthology.org/N16-1034)
-- [ ] [NAACL, 2016] [Expectation-Regulated Neural Model for Event Mention Extraction](https://aclanthology.org/N16-1045)
-- [ ] [NAACL, 2016] [Bidirectional RNN for Medical Event Detection in Electronic Health Records](https://aclanthology.org/N16-1056)
-- [ ] [NAACL, 2016] [Cross-genre Event Extraction with Knowledge Enrichment](https://aclanthology.org/N16-1137)
-- [ ] [NAACL, 2016] [Cross-media Event Extraction and Recommendation](https://aclanthology.org/N16-3015)
-- [ ] [NAACL, 2015] [Diamonds in the Rough: Event Extraction from Imperfect Microblog Data](https://aclanthology.org/N15-1066)
-- [ ] [TACL, 2015] [Exploiting Parallel News Streams for Unsupervised Event Extraction](https://aclanthology.org/Q15-1009)
-- [ ] [TACL, 2015] [Large-Scale Information Extraction from Textual Definitions through Deep Syntactic and Semantic Analysis](https://aclanthology.org/Q15-1038)
-- [ ] [EMNLP, 2015] [Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists](https://aclanthology.org/D15-1060)
-- [ ] [EMNLP, 2015] [Inferring Binary Relation Schemas for Open Information Extraction](https://aclanthology.org/D15-1065)
-- [ ] [EMNLP, 2015] [Event Detection and Factuality Assessment with Non-Expert Supervision](https://aclanthology.org/D15-1189)
-- [ ] [EMNLP, 2015] [Abstractive Multi-document Summarization with Semantic Information Extraction](https://aclanthology.org/D15-1219)
-- [ ] [EMNLP, 2015] [Twitter-scale New Event Detection via K-term Hashing](https://aclanthology.org/D15-1310)
-- [ ] [EMNLP, 2015] [Transparent Machine Learning for Information Extraction: State-of-the-Art and the Future](https://aclanthology.org/D15-2003)
-- [ ] [ACL, 2015] [Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks](https://aclanthology.org/P15-1017)
-- [ ] [ACL, 2015] [Leveraging Linguistic Structure For Open Domain Information Extraction](https://aclanthology.org/P15-1034)
-- [ ] [ACL, 2015] [Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approach](https://aclanthology.org/P15-1035)
-- [ ] [ACL, 2015] [A Lexicalized Tree Kernel for Open Information Extraction](https://aclanthology.org/P15-2046)
-- [ ] [ACL, 2015] [Event Detection and Domain Adaptation with Convolutional Neural Networks](https://aclanthology.org/P15-2060)
-- [ ] [ACL, 2015] [Disease Event Detection based on Deep Modality Analysis](https://aclanthology.org/P15-3005)
-- [ ] [ACL, 2015] [A Domain-independent Rule-based Framework for Event Extraction](https://aclanthology.org/P15-4022)
-- [ ] [NAACL, 2015] [Exploring Relational Features and Learning under Distant Supervision for Information Extraction Tasks](https://aclanthology.org/N15-2006)
-- [ ] [NAACL, 2015] [ICE: Rapid Information Extraction Customization for NLP Novices](https://aclanthology.org/N15-3007)
-- [ ] [EMNLP, 2014] [Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features](https://aclanthology.org/D14-1090)
-- [ ] [EMNLP, 2014] [Exploiting Community Emotion for Microblog Event Detection](https://aclanthology.org/D14-1123)
-- [ ] [EMNLP, 2014] [Event Role Extraction using Domain-Relevant Word Representations](https://aclanthology.org/D14-1199)
-- [ ] [EMNLP, 2014] [Combining Visual and Textual Features for Information Extraction from Online Flyers](https://aclanthology.org/D14-1206)
-- [ ] [EMNLP, 2014] [Major Life Event Extraction from Twitter based on Congratulations/Condolences Speech Acts](https://aclanthology.org/D14-1214)
-- [ ] [COLING, 2014] [Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction](https://aclanthology.org/C14-1204)
-- [ ] [COLING, 2014] [Comparable Study of Event Extraction in Newswire and Biomedical Domains](https://aclanthology.org/C14-1214)
-- [ ] [ACL, 2014] [Information Extraction over Structured Data: Question Answering with Freebase](https://aclanthology.org/P14-1090)
-- [ ] [ACL, 2014] [A Simple Bayesian Modelling Approach to Event Extraction from Twitter](https://aclanthology.org/P14-2114)
-- [ ] [ACL, 2014] [Open Information Extraction for Spanish Language based on Syntactic Constraints](https://aclanthology.org/P14-3011)
-- [ ] [TACL, 2013] [Modeling Missing Data in Distant Supervision for Information Extraction](https://aclanthology.org/Q13-1030)
-- [ ] [EMNLP, 2013] [Rule-Based Information Extraction is Dead! Long Live Rule-Based Information Extraction Systems!](https://aclanthology.org/D13-1079)
-- [ ] [ACL, 2013] [Joint Event Extraction via Structured Prediction with Global Features](https://aclanthology.org/P13-1008)
-- [ ] [ACL, 2013] [Argument Inference from Relevant Event Mentions in Chinese Argument Extraction](https://aclanthology.org/P13-1145)
-- [ ] [ACL, 2013] [Argument Inference from Relevant Event Mentions in Chinese Argument Extraction](https://aclanthology.org/P13-1145)
-- [ ] [ACL, 2013] [Propminer: A Workflow for Interactive Information Extraction and Exploration using Dependency Trees](https://aclanthology.org/P13-4027)
-- [ ] [NAACL, 2013] [Open Information Extraction with Tree Kernels](https://aclanthology.org/N13-1107)
-- [ ] [COLING, 2012] [Joint Modeling for Chinese Event Extraction with Rich Linguistic Features](https://aclanthology.org/C12-1033)
-- [ ] [COLING, 2012] [Employing Morphological Structures and Sememes for Chinese Event Extraction](https://aclanthology.org/C12-1099)
-- [ ] [COLING, 2012] [Joint Modeling of Trigger Identification and Event Type Determination in Chinese Event Extraction](https://aclanthology.org/C12-1100)
-- [ ] [COLING, 2012] [ISO-TimeML Event Extraction in Persian Text](https://aclanthology.org/C12-1179)
-- [ ] [COLING, 2012] [Parenthetical Classification for Information Extraction](https://aclanthology.org/C12-2030)
-- [ ] [COLING, 2012] [Sourcing the Crowd for a Few Good Ones: Event Type Detection](https://aclanthology.org/C12-2121)
-- [ ] [COLING, 2012] [Optimal Scheduling of Information Extraction Algorithms](https://aclanthology.org/C12-2125)
-- [ ] [COLING, 2012] [Open Information Extraction for SOV Language Based on Entity-Predicate Pair Detection](https://aclanthology.org/C12-3038)
-- [ ] [COLING, 2012] [Markov Chains for Robust Graph-Based Commonsense Information Extraction](https://aclanthology.org/C12-3055)
-- [ ] [ACL, 2012] [Automatic Event Extraction with Structured Preference Modeling](https://aclanthology.org/P12-1088)
-- [ ] [ACL, 2012] [A Novel Burst-based Text Representation Model for Scalable Event Detection](https://aclanthology.org/P12-2009)
-- [ ] [ACL, 2012] [ACCURAT Toolkit for Multi-Level Alignment and Information Extraction from Comparable Corpora](https://aclanthology.org/P12-3016)
-- [ ] [ACL, 2012] [WizIE: A Best Practices Guided Development Environment for Information Extraction](https://aclanthology.org/P12-3019)
-- [ ] [EMNLP, 2012] [Open Language Learning for Information Extraction](https://aclanthology.org/D12-1048)
-- [ ] [EMNLP, 2012] [Employing Compositional Semantics and Discourse Consistency in Chinese Event Extraction](https://aclanthology.org/D12-1092)
-- [ ] [EMNLP, 2012] [Building a Lightweight Semantic Model for Unsupervised Information Extraction on Short Listings](https://aclanthology.org/D12-1099)
-- [ ] [NAACL, 2012] [A Weighting Scheme for Open Information Extraction](https://aclanthology.org/N12-2011)
-- [ ] [EMNLP, 2011] [Fast and Robust Joint Models for Biomedical Event Extraction](https://aclanthology.org/D11-1001)
-- [ ] [EMNLP, 2011] [Unsupervised Information Extraction with Distributional Prior Knowledge](https://aclanthology.org/D11-1075)
-- [ ] [EMNLP, 2011] [Identifying Relations for Open Information Extraction](https://aclanthology.org/D11-1142)
-- [ ] [ACL, 2011] [Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations](https://aclanthology.org/P11-1055)
-- [ ] [ACL, 2011] [Template-Based Information Extraction without the Templates](https://aclanthology.org/P11-1098)
-- [ ] [ACL, 2011] [Using Cross-Entity Inference to Improve Event Extraction](https://aclanthology.org/P11-1113)
-- [ ] [ACL, 2011] [Event Extraction as Dependency Parsing](https://aclanthology.org/P11-1163)
-- [ ] [ACL, 2011] [Can Document Selection Help Semi-supervised Learning? A Case Study On Event Extraction](https://aclanthology.org/P11-2045)
-- [ ] [ACL, 2011] [SystemT: A Declarative Information Extraction System](https://aclanthology.org/P11-4019)
-- [ ] [EMNLP, 2010] [Evaluating the Impact of Alternative Dependency Graph Encodings on Solving Event Extraction Tasks](https://aclanthology.org/D10-1096)
-- [ ] [COLING, 2010] [Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon Production](https://aclanthology.org/C10-1006)
-- [ ] [COLING, 2010] [Filtered Ranking for Bootstrapping in Event Extraction](https://aclanthology.org/C10-1077)
-- [ ] [COLING, 2010] [Evaluating Dependency Representations for Event Extraction](https://aclanthology.org/C10-1088)
-- [ ] [COLING, 2010] [Challenges from Information Extraction to Information Fusion](https://aclanthology.org/C10-2058)
-- [ ] [COLING, 2010] [Enhancing Multi-lingual Information Extraction via Cross-Media Inference and Fusion](https://aclanthology.org/C10-2072)
-- [ ] [COLING, 2010] [“Expresses-an-opinion-about”: using corpus statistics in an information extraction approach to opinion mining](https://aclanthology.org/C10-2126)
-- [ ] [COLING, 2010] [Shallow Information Extraction from Medical Forum Data](https://aclanthology.org/C10-2133)
-- [ ] [ACL, 2010] [Open Information Extraction Using Wikipedia](https://aclanthology.org/P10-1013)
-- [ ] [ACL, 2010] [SystemT: An Algebraic Approach to Declarative Information Extraction](https://aclanthology.org/P10-1014)
-- [ ] [ACL, 2010] [Using Document Level Cross-Event Inference to Improve Event Extraction](https://aclanthology.org/P10-1081)
-- [ ] [ACL, 2010] [An Entity-Level Approach to Information Extraction](https://aclanthology.org/P10-2054)
-- [ ] [NAACL, 2010] [Utility Evaluation of Cross-document Information Extraction](https://aclanthology.org/N10-1036)
-- [ ] [NAACL, 2010] [Constraint-Driven Rank-Based Learning for Information Extraction](https://aclanthology.org/N10-1111)
-- [ ] [EMNLP, 2009] [A Unified Model of Phrasal and Sentential Evidence for Information Extraction](https://aclanthology.org/D09-1016)
-- [ ] [ACL, 2009] [Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm](https://aclanthology.org/P09-1061)
-- [ ] [ACL, 2009] [Mining Association Language Patterns for Negative Life Event Classification](https://aclanthology.org/P09-2051)
-- [ ] [NAACL, 2009] [A Local Tree Alignment-based Soft Pattern Matching Approach for Information Extraction](https://aclanthology.org/N09-2043)
-- [ ] [NAACL, 2009] [Language Specific Issue and Feature Exploration in Chinese Event Extraction](https://aclanthology.org/N09-2053)
-- [ ] [NAACL, 2009] [Solving the “Who’s Mark Johnson Puzzle”: Information Extraction Based Cross Document Coreference](https://aclanthology.org/N09-3002)
-- [ ] [CL, 2008] [Book Reviews: Information Extraction: Algorithms and Prospects in a Retrieval Context by Marie-Francine Moens](https://aclanthology.org/J08-2008)
-- [ ] [EMNLP, 2008] [Regular Expression Learning for Information Extraction](https://aclanthology.org/D08-1003)
-- [ ] [COLING, 2008] [Investigating Statistical Techniques for Sentence-Level Event Classification](https://aclanthology.org/C08-1078)
-- [ ] [COLING, 2008] [Event Frame Extraction Based on a Gene Regulation Corpus](https://aclanthology.org/C08-1096)
-- [ ] [ACL, 2008] [Refining Event Extraction through Cross-Document Inference](https://aclanthology.org/P08-1030)
-- [ ] [EMNLP, 2007] [Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions](https://aclanthology.org/D07-1075)
-- [ ] [EMNLP, 2007] [Bootstrapping Information Extraction from Field Books](https://aclanthology.org/D07-1087)
-- [ ] [ACL, 2007] [A Multi-resolution Framework for Information Extraction from Free Text](https://aclanthology.org/P07-1075)
-- [ ] [ACL, 2007] [Sparse Information Extraction: Unsupervised Language Models to the Rescue](https://aclanthology.org/P07-1088)
-- [ ] [ACL, 2007] [System Demonstration of On-Demand Information Extraction](https://aclanthology.org/P07-2005)
-- [ ] [NAACL, 2007] [Question Answering Using Integrated Information Retrieval and Information Extraction](https://aclanthology.org/N07-1067)
-- [ ] [NAACL, 2007] [A High Accuracy Method for Semi-Supervised Information Extraction](https://aclanthology.org/N07-2043)
-- [ ] [NAACL, 2007] [TextRunner: Open Information Extraction on the Web](https://aclanthology.org/N07-4013)
-- [ ] [EMNLP, 2006] [Automatic Construction of Predicate-argument Structure Patterns for Biomedical Information Extraction](https://aclanthology.org/W06-1634)
-- [ ] [EMNLP, 2006] [Unsupervised Information Extraction Approach Using Graph Mutual Reinforcement](https://aclanthology.org/W06-1659)
-- [ ] [EMNLP, 2006] [Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger](https://aclanthology.org/W06-1670)
-- [ ] [COLING, 2006] [Segment-Based Hidden Markov Models for Information Extraction](https://aclanthology.org/P06-1061)
-- [ ] [COLING, 2006] [Event Extraction in a Plot Advice Agent](https://aclanthology.org/P06-1108)
-- [ ] [COLING, 2006] [ARE: Instance Splitting Strategies for Dependency Relation-Based Information Extraction](https://aclanthology.org/P06-2074)
-- [ ] [COLING, 2006] [On-Demand Information Extraction](https://aclanthology.org/P06-2094)
-- [ ] [NAACL, 2006] [Preemptive Information Extraction using Unrestricted Relation Discovery](https://aclanthology.org/N06-1039)
-- [ ] [NAACL, 2006] [A Comparison of Tagging Strategies for Statistical Information Extraction](https://aclanthology.org/N06-2038)
-- [ ] [ACL, 2005] [Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling](https://aclanthology.org/P05-1045)
-- [ ] [ACL, 2005] [Unsupervised Learning of Field Segmentation Models for Information Extraction](https://aclanthology.org/P05-1046)
-- [ ] [ACL, 2005] [Multi-Field Information Extraction and Cross-Document Fusion](https://aclanthology.org/P05-1060)
-- [ ] [ACL, 2005] [Resume Information Extraction with Cascaded Hybrid Model](https://aclanthology.org/P05-1062)
-- [ ] [COLING, 2004] [Cascading Use of Soft and Hard Matching Pattern Rules for Weakly Supervised Information Extraction](https://aclanthology.org/C04-1078)
-- [ ] [COLING, 2004] [Information Extraction from Single and Multiple Sentences](https://aclanthology.org/C04-1126)
-- [ ] [COLING, 2004] [Cross-lingual Information Extraction System Evaluation](https://aclanthology.org/C04-1127)
-- [ ] [COLING, 2004] [Information Extraction for Question Answering: Improving Recall Through Syntactic Patterns](https://aclanthology.org/C04-1188)
-- [ ] [NAACL, 2004] [Accurate Information Extraction from Research Papers using Conditional Random Fields](https://aclanthology.org/N04-1042)
-- [ ] [NAACL, 2004] [Confidence Estimation for Information Extraction](https://aclanthology.org/N04-4028)
-- [ ] [ACL, 2004] [Mining Metalinguistic Activity in Corpora to Create Lexical Resources Using Information Extraction Techniques: the MOP System](https://aclanthology.org/P04-1028)
-- [ ] [ACL, 2004] [Collective Information Extraction with Relational Markov Networks](https://aclanthology.org/P04-1056)
-- [ ] [ACL, 2004] [Weakly Supervised Learning for Cross-document Person Name Disambiguation Supported by Information Extraction](https://aclanthology.org/P04-1076)
-- [ ] [ACL, 2004] [Combining Lexical, Syntactic, and Semantic Features with Maximum Entropy Models for Information Extraction](https://aclanthology.org/P04-3022)
-- [ ] [NAACL, 2003] [Story Link Detection and New Event Detection are Asymmetric](https://aclanthology.org/N03-2005)
-- [ ] [NAACL, 2003] [pre-CODIE–Crosslingual On-Demand Information Extraction](https://aclanthology.org/N03-4013)
-- [ ] [ACL, 2003] [Using Predicate-Argument Structures for Information Extraction](https://aclanthology.org/P03-1002)
-- [ ] [ACL, 2003] [Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods](https://aclanthology.org/P03-1028)
-- [ ] [ACL, 2003] [Optimizing Story Link Detection is not Equivalent to Optimizing New Event Detection](https://aclanthology.org/P03-1030)
-- [ ] [ACL, 2003] [Integrating Information Extraction and Automatic Hyperlinking](https://aclanthology.org/P03-2019)
-- [ ] [COLING, 2002] [Inducing Information Extraction Systems for New Languages via Cross-language Projection](https://aclanthology.org/C02-1070)
-- [ ] [COLING, 2002] [Location Normalization for Information Extraction](https://aclanthology.org/C02-1127)
-- [ ] [COLING, 2002] [Semantic Case Role Detection for Information Extraction](https://aclanthology.org/C02-2011)
-- [ ] [EMNLP, 2002] [Information Extraction from Voicemail Transcripts](https://aclanthology.org/W02-1041)
-- [ ] [EMNLP, 2001] [Information Extraction Using the Structured Language Model](https://aclanthology.org/W01-0510)
-- [ ] [ACL, 2001] [Information Extraction from Voicemail](https://aclanthology.org/P01-1039)
-- [ ] [COLING, 2000] [Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP](https://aclanthology.org/C00-2101)
-- [ ] [COLING, 2000] [Automatic Acquisition of Domain Knowledge for Information Extraction](https://aclanthology.org/C00-2136)
-- [ ] [COLING, 2000] [The Week at a Glance - Cross-language Cross-document Information Extraction and Translation](https://aclanthology.org/C00-2147)
-- [ ] [ACL, 2000] [Invited Talk: Generic NLP Technologies: Language, Knowledge and Information Extraction](https://aclanthology.org/P00-1002)
-- [ ] [ACL, 2000] [From Information Retrieval to Information Extraction](https://aclanthology.org/W00-1109)
-- [ ] [ACL, 1999] [Automatic Speech Recognition and Its Application to Information Extraction](https://aclanthology.org/P99-1002)
-- [ ] [COLING, 1998] [Toward General-Purpose Learning for Information Extraction](https://aclanthology.org/C98-1064)
-- [ ] [ACL, 1998] [Toward General-Purpose Learning for Information Extraction](https://aclanthology.org/P98-1067)
-- [ ] [EMNLP, 1997] [Probabilistic Coreference in Information Extraction](https://aclanthology.org/W97-0319)
-- [ ] [ACL, 1995] [Constraint-Based Event Recognition for Information Extraction](https://aclanthology.org/P95-1042)
-- [ ] [ACL, 1995] [Constraint-Based Event Recognition for Information Extraction](https://aclanthology.org/P95-1042)
-- [ ] [COLING, 1994] [Pattern Matching in the TEXTRACT Information Extraction System](https://aclanthology.org/C94-2173)
-- [ ] [CL, 1993] [Book Reviews:Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval](https://aclanthology.org/J93-1012)
-- [ ] [COLING, 1990] [Information Extraction and Semantic Constraints](https://aclanthology.org/C90-3071)

run.py

@@ -1,7 +1,10 @@
 from src.interfaces.aclanthology import AclanthologyPaperList
 from src.interfaces.arxiv import ArxivPaperList
 from src.interfaces.dblp import DblpPaperList
-from src.utils import dump_paper_list_to_markdown_checklist
+from src.utils import (
+    dump_paper_list_to_markdown_checklist,
+    dump_paper_list_to_jsonlines,
+)
 
 if __name__ == "__main__":
     # use `bash scripts/get_aclanthology.sh` to download and prepare anthology data first
@@ -15,6 +18,8 @@ if __name__ == "__main__":
             ["event", "classification"],
             ["event", "tracking"],
             ["event", "relation", "extraction"],
+            ["event", "prediction"],
+            ["script", "learning"],
         ],
         "venue": [
             ["acl"],
@@ -28,6 +33,7 @@ if __name__ == "__main__":
     }
     ee_papers = acl_paper_list.search(ee_query)
     dump_paper_list_to_markdown_checklist(ee_papers, "results/ee-paper-list.md")
+    dump_paper_list_to_jsonlines(ee_papers, "results/ee-paper-list.jsonl")
 
     doc_query = {
         "title": [
@@ -45,6 +51,7 @@ if __name__ == "__main__":
     }
     doc_papers = acl_paper_list.search(doc_query)
     dump_paper_list_to_markdown_checklist(doc_papers, "results/doc-paper-list.md")
+    dump_paper_list_to_jsonlines(doc_papers, "results/doc-paper-list.jsonl")
 
     # arxiv papers
     arxiv_paper_list = ArxivPaperList(
@@ -54,6 +61,7 @@ if __name__ == "__main__":
             "Event Extraction OR Event Argument Extraction OR Event Detection"
             " OR Event Classification OR Event Tracking"
             " OR Event Relation Extraction OR Information Extraction"
+            " OR Event Prediction OR Script Learning"
         ),
         category="cs.CL",
     )
@@ -66,6 +74,8 @@ if __name__ == "__main__":
             ["event", "classification"],
             ["event", "tracking"],
             ["event", "relation", "extraction"],
+            ["event", "prediction"],
+            ["script", "learning"],
         ],
         "venue": [
             ["cs.CL"],
@@ -75,12 +85,16 @@ if __name__ == "__main__":
     dump_paper_list_to_markdown_checklist(
         arxiv_ee_papers, "results/arxiv-ee-paper-list.md"
     )
+    dump_paper_list_to_jsonlines(
+        arxiv_ee_papers, "results/arxiv-ee-paper-list.jsonl"
+    )
 
     # dblp papers
     dblp_paper_list = DblpPaperList(
         "./cache/dblp.json",
         use_cache=True,
-        query="Event Extraction",
+        query="Event|Information|Argument|Script Extraction|Classification|Tracking|Prediction|Learning",
+        max_results=50000,
     )
     dblp_ee_query = {
         "title": [
@@ -91,6 +105,8 @@ if __name__ == "__main__":
             ["event", "classification"],
             ["event", "tracking"],
             ["event", "relation", "extraction"],
+            ["event", "prediction"],
+            ["script", "learning"],
         ],
         "venue": [
             ["aaai"],
@@ -108,3 +124,6 @@ if __name__ == "__main__":
     dump_paper_list_to_markdown_checklist(
         dblp_ee_papers, "results/dblp-ee-paper-list.md"
     )
+    dump_paper_list_to_jsonlines(
+        dblp_ee_papers, "results/dblp-ee-paper-list.jsonl"
+    )

src/engine.py

@@ -33,8 +33,6 @@ class SearchAPI:
                             paper_indices.append(i)
                 papers = [papers[i] for i in paper_indices]
 
-        if papers:
-            papers = sorted(papers, key=lambda p: (p.year, p.month), reverse=True)
         return papers
 
     def search(
@@ -58,10 +56,15 @@ class SearchAPI:
         Returns:
             a list of `Paper`
         """
+        papers = []
         if method == "exhausted":
-            return self.exhausted_search(query)
+            papers = self.exhausted_search(query)
         else:
             raise NotImplementedError
 
+        if papers:
+            papers = sorted(set(papers), key=lambda p: (p.year, p.month), reverse=True)
+        return papers
+
     def tokenize(self, string: str) -> list[str]:
         return string.lower().split()

src/interfaces/__init__.py

@@ -22,5 +22,18 @@ class Paper:
             "venue": self.venue,
         }
 
+    def as_tuple(self) -> tuple:
+        return (
+            self.title,
+            self.authors,
+            self.abstract,
+            self.url,
+            self.doi,
+            self.venue,
+        )
+
     def __getitem__(self, attr_key: str):
         return getattr(self, attr_key)
+
+    def __hash__(self) -> int:
+        return hash(self.as_tuple())

src/utils.py

@@ -122,6 +122,24 @@ def dump_json(data: list | dict, filepath: str | pathlib.Path):
         json.dump(data, fout, ensure_ascii=False)
 
 
+def load_jsonlines(filepath, **kwargs):
+    data = list()
+    with open(filepath, "rt", encoding="utf-8") as fin:
+        for line in fin:
+            line_data = json.loads(line.strip())
+            data.append(line_data)
+    return data
+
+
+def dump_jsonlines(obj, filepath, **kwargs):
+    with open(filepath, "wt", encoding="utf-8") as fout:
+        for d in obj:
+            line_d = json.dumps(
+                d, ensure_ascii=False, **kwargs
+            )
+            fout.write("{}\n".format(line_d))
+
+
 def dump_list_to_markdown_checklist(str_list: list[str], filepath: str | pathlib.Path):
     md_string = ""
     for string in str_list:
@@ -144,6 +162,13 @@ def dump_paper_list_to_markdown_checklist(papers: list[Paper], filepath: str | p
     dump_list_to_markdown_checklist(string_list, filepath)
 
 
+def dump_paper_list_to_jsonlines(papers: list[Paper], filepath: str | pathlib.Path):
+    dump = []
+    for paper in papers:
+        dump.append(paper.as_dict())
+    dump_jsonlines(dump, filepath)
+
+
 if __name__ == "__main__":
     parse_bib(
         pathlib.Path("cache/anthology+abstracts.bib.gz"),