arXiv:2010.14576
공식 코드 · Papers with Code
WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols
원문 초록
This paper presents the results of the wet lab information extraction task at WNUT 2020. This task consisted of two sub tasks: (1) a Named Entity Recognition (NER) task with 13 participants and (2) a Relation Extraction (RE) task with 2 participants. We outline the task, data annotation process, corpus statistics, and provide a high-level overview of the participating systems for each sub task.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition
Zero-Shot Document-Level Biomedical Relation Extraction via Scenario-based Prompt Design in Two-Stage with LLM
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning
CRENER: A Character Relation Enhanced Chinese NER Model
AI-assisted Knowledge Discovery in Biomedical Literature to Support Decision-making in Precision Oncology
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.