update metadata

README.md

@@ -7,7 +7,7 @@ task_categories:
 - text-retrieval
 - other
 pretty_name: BioKGBench
-size_categories: 1G<n<100G
+size_categories: 10K<n<100K
 annotations_creators: 
 - expert-generated
 - machine-generated
@@ -38,21 +38,26 @@ configs:
       path: kgqa/dev.json
     - split: test
       path: kgqa/test.json
-  - config_name: scv
+  - config_name: scv-corpus
     data_files:
       - split: corpus
         path: scv/merged_corpus.jsonl
+  - config_name: scv
+    data_files:
       - split: dev
         path: scv/dev.jsonl
       - split: test
         path: scv/test.jsonl
   - config_name: biokg
     data_files:
-    - split: data
-      path: bioKG/*/*.tsv
+    - split: datasets
+      path: bioKG/datasets/*.tsv
+    - split: ontologies
+      path: bioKG/ontologies/*.tsv
 tags:
   - agent
   - medical
+arxiv: 2407.00466
 ---
 
 # Agent4S-BioKG
@@ -62,7 +67,7 @@ A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science.
     <img src="https://img.shields.io/badge/license-MIT-blue" /></a>
     
 <a href="https://github.com/westlake-autolab/Agent4S-BioKG" alt="license">
-   Github </a>
+    <img src="/assets/img/github-mark.png" /> Github </a>
 </p>
 
 ## Introduction
@@ -72,58 +77,23 @@ In contrast to traditional evaluation benchmark that only focuses on factual QA,
 
 ## Overview
 <details open>
-<summary>Tasks</summary>
+<summary>Dataset(Need to <a href="https://huggingface.co/datasets/AutoLab-Westlake/BioKGBench-Dataset">download</a> from huggingface)</summary>
 
+* **bioKG**: The knowledge graph used in the dataset.
 * **KGCheck**: Given a knowledge graph and a scientific claim, the agent needs to check whether the claim is supported by the knowledge graph. The agent can interact with the knowledge graph by asking questions and receiving answers.
+  * **Dev**: 20 samples
+  * **Test**: 205 samples
+  * **corpus**: 51 samples
 * **KGQA**: Given a knowledge graph and a question, the agent needs to answer the question based on the knowledge graph.
+  * **Dev**: 60 samples
+  * **Test**: 638 samples
 * **SCV**: Given a scientific claim and a research paper, the agent needs to check whether the claim is supported by the research paper.
+  * **Dev**: 120 samples
+  * **Test**: 1265 samples
+  * **corpus**: 5664 samples
 
 </details>
 
-<details open>
-<summary>Code Structure</summary>
-</details>
-
-<details open>
-<summary>Baseline</summary>
-</details>
-
-<details open>
-<summary>Dataset</summary>
-</details>
-
-## News and Updates
-[2024-06-06] `BioKGBench` v0.1.0 is released.
-
-## Installation
-This project has provided an environment setting file of conda, users can easily reproduce the environment by the following commands:
-```bash
-conda create -n agent4s-biokg python=3.10
-conda activate agent4s-biokg
-pip install -r requirements.txt
-```
-
-## Getting Started
-
-**Obtaining dataset**:
-The dataset can be found in the [release]. The dataset is divided into three parts: `KGCheck`, `KGQA`, and `SCV`, every part is split into `Dev` and `Test`.
-
-**Running Baseline**:
-
-* `KGCheck`:
-```bash
-```
-* `KGQA`:
-```bash
-```
-* `SCV`:
-```bash
-```
-
-## Acknowledgement
-
-`BioKGBench` is an open-source project for Agent evaluation created by researchers in **Westlake Auto Lab** and **CAIRI Lab**. We encourage researchers interested in LLM Agent and other related fields to contribute to this project!
-
 ## Citation
 
 ## Contact
@@ -133,8 +103,3 @@ For adding new features, looking for helps, or reporting bugs associated with `B
 - Siqi Ma([email protected]), Westlake University
 - Junjie Shan([email protected]), Westlake University
 - Xiaojing Zhang([email protected]), Westlake University
-
-## TODO
-
-1. Update dataset
-2. Support pip installation