Datasets:
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### Dataset Summary
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This is a reproduced (i.e. after web-crawling) and processed version of [the "PropSegment" dataset](https://github.com/google-research-datasets/PropSegmEnt) from Google Research.
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PropSegment (Proposition-level Segmentation and Entailment) is a large-scale, human annotated dataset for segmenting English text into propositions, and recognizing proposition-level entailment relations --- whether a different, related document entails each proposition, contradicts it, or neither.
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The dataset features >45k human annotated propositions, i.e. individual semantic units within sentences, as well as >35k entailment labels between propositions and documents.
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Check out more details in the [dataset paper](https://arxiv.org/abs/2212.10750).
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## Dataset Structure
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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### Dataset Summary
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This is a reproduced (i.e. after web-crawling) and processed version of [the "PropSegment" dataset](https://github.com/google-research-datasets/PropSegmEnt) from Google Research.
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Since the [`News`](https://github.com/google-research-datasets/NewSHead) portion of the dataset is released only via urls, we reconstruct the dataset by crawling.
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Overall, ~96% of the dataset can be reproduced, and the rest ~4% either have url no longer valid, or sentences that have been edited (i.e. cannot be aligned with the orignial dataset).
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PropSegment (Proposition-level Segmentation and Entailment) is a large-scale, human annotated dataset for segmenting English text into propositions, and recognizing proposition-level entailment relations --- whether a different, related document entails each proposition, contradicts it, or neither.
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The original dataset features >45k human annotated propositions, i.e. individual semantic units within sentences, as well as >35k entailment labels between propositions and documents.
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Check out more details in the [dataset paper](https://arxiv.org/abs/2212.10750).
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## Dataset Structure
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Here we provide processed versions of the dataset for seq2seq model inputs/outputs.
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`proposition_segmentation.*.jsonl` contains data for the text segmentation task, i.e. split a sentence into propositions.
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The output propositions are concatenated as one string (with no particular order between them) by a special token `[SEP]`.
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Each proposition is annotated as spans enclosed by `[M]` and `[/M]`.
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```
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{
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"sentence": "This film marks the directorial debut for production designer Robert Stromberg.",
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"propositions": "This film marks the directorial debut for [M]production designer Robert Stromberg.[/M][SEP]This [M]film marks the directorial debut for[/M] production designer [M]Robert Stromberg[/M]."
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}
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```
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### Citation
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@inproceedings{chen2023propsegment,
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title = "{PropSegmEnt}: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition",
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author = "Chen, Sihao and Buthpitiya, Senaka and Fabrikant, Alex and Roth, Dan and Schuster, Tal",
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booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
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year = "2023",
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}
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