Text · dataset · 2022
MEDIQA RQE
Listed in Hugging Face Datasets
Description
The MEDIQA challenge is an ACL-BioNLP 2019 shared task aiming to attract further research efforts in Natural Language Inference (NLI), Recognizing Question Entailment (RQE), and their applications in medical Question Answering (QA). Mailing List: groups.google.com/forum/#!forum/bionlp-mediqa The objective of the RQE task is to identify entailment between two questions in the context of QA. We use the following definition of question entailment: “a question A entails a question B if every answer to B is also a complete or partial answer to A” [1] [1] A. Ben Abacha & D. Demner-Fushman. “Recognizing Question Entailment for Medical Question Answering”.
AMIA 2016.
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/bigbio/mediqa_rqe ↗
landing page · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/bigbio/mediqa_rqe ↗
metadata API · from Hugging Face
Topics
- Stated by source
- text
- From keywords
- Computer Science & AI
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | bigbio/mediqa_rqe | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| concepts[modality].hf_modality:text | source · Hugging Face | connector:huggingface@1.0.0 | |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| license_text | source · Hugging Face | connector:huggingface@1.0.0 | |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |