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Natural Language Processing
Published in Rakesh M. Verma, David J. Marchette, Cybersecurity Analytics, 2019
Rakesh M. Verma, David J. Marchette
MUC/DUC Corpora: The seven Message Understanding Conferences (MUCs) were competitions involving information extraction that were organized by National Institute of Standards and Technology (NIST). The Document Understanding Conference (DUC) series have created corpora for evaluating automatic text summarization and question answering systems. The DUC corpora consist of single news articles with human summaries, or batches of news articles on a single topic with various types and sizes of human summaries. The single document summarization competition was abandoned after two years, since a baseline summary consisting of the first 100 words of the article was very hard to beat. See [456] for limits on the recall score possible on DUC document summarization tasks. The DUC series was succeeded by the Text Analysis Conferences (TAC). In TAC, the tasks changed to update summarization and question answering.
Full-span named entity recognition with boundary regression
Published in Connection Science, 2023
Junhui Yu, Yanping Chen, Qinghua Zheng, Yuefei Wu, Ping Chen
A named entity is defined as a word or a phrase in a sentence that refers to an object in the world. From the perspective of natural language understanding, named entity is the most basic linguistic units of a sentence. Recognising them is the key to understanding a sentence. This task was first coined in the sixth Message Understanding Conference (MUC-6) as a subtask of information extraction (Grishman & Sundheim, 1996). As a fundamental task, it can support a wide range of applications, e.g. knowledge graph construction (Al-Moslmi et al., 2020), machine translation (Hu et al., 2022), sentence parsing (Yu et al., 2020), question answering (Longpre et al., 2021), and so forth. Furthermore, named entities comprise the main part of out-of-vocabulary words (or new words) which are usually noted as a considerable obstacle to automatically processing natural language. Therefore, techniques of named entity recognition also have important theoretical impacts and applications in natural language processing.