Analysis of Clinical Text: Task 14 of SemEval 2015

SemEval (Semantic Evaluation) is an ongoing series of evaluations of computational semantic analysis systems, organized under the umbrella of SIGLEX, the Special Interest Group on the Lexicon of the Association for Computational Linguistics. This project describes Task 14 ("Analysis of Clinical Text") of the International Workshop on Semantic Evaluation 2015 (SemEval 2015). The purpose of Task 14 is to enhance current research in natural language processing (NLP) methods used in the clinical domain, and to introduce clinical text processing to the broader NLP community. The task aims to combine supervised methods for text analysis with unsupervised approaches. More specifically, the task aims to combine supervised methods for entity/acronym/abbreviation recognition and mapping to Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) with access to larger clinical corpus for utilizing unsupervised techniques. Additionally, it will also evaluate systems on the task of template filling, which involves the population of eight attributes of the identified disorders with their normalized values.

语义评测研讨会（SemEval, Semantic Evaluation）是一项持续开展的计算语义分析系统评测系列活动，由国际计算语言学协会（Association for Computational Linguistics, ACL）下设的词汇领域专业兴趣组（SIGLEX, Special Interest Group on the Lexicon）主办。本项目介绍2015年国际语义评测研讨会（SemEval 2015）的任务14——“临床文本分析”。任务14的核心目标在于推动临床领域自然语言处理（Natural Language Processing, NLP）方法的现有研究进展，并向更广泛的NLP学界推广临床文本处理技术。该任务旨在将文本分析的监督式方法与无监督式方法进行融合。具体而言，本任务要求将实体、首字母缩略词与缩写识别及映射至统一医学语言系统（Unified Medical Language System, UMLS）概念唯一标识符（Concept Unique Identifiers, CUIs）的监督式方法，结合可访问的大规模临床语料库以应用无监督技术。此外，本次评测还将覆盖模板填充任务，即基于标准化取值为已识别的病症填充八项属性。