About Neural Networks and Writing Definitions

Q2 Arts and Humanities Dictionaries Pub Date : 2022-01-06 DOI:10.1353/dic.2021.0022
Timothee Mickus, Mathieu Constant, Denis Paperno
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引用次数: 2

Abstract

ABSTRACT:In this article, we describe the current state of the field of NLP (Natural Language Processing) and detail the applications and trends that are of interest to lexicographers. We begin with a brief overview of how dictionaries have been used in the NLP community, particularly to introduce semantic knowledge in NLP systems. We follow up with a detailed account of one of the most well-known types of NLP semantic representations, namely word embeddings, and some of their limitations—in particular, how they fail to relate words to real-world objects. We then argue that the task of Definition Modeling, which consists of generating dictionary definitions from word embeddings, is well suited to studying these limitations and highlight how current issues in automated evaluation of NLP systems specifically hinder this investigation.
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关于神经网络和写作定义
摘要:在本文中,我们介绍了自然语言处理领域的现状,并详细介绍了词典编纂者感兴趣的应用和趋势。我们首先简要概述了字典是如何在NLP社区中使用的,特别是在NLP系统中引入语义知识。接下来,我们详细介绍了最著名的NLP语义表示类型之一,即单词嵌入,以及它们的一些局限性,特别是它们如何无法将单词与现实世界的对象联系起来。然后,我们认为定义建模的任务,包括从单词嵌入中生成字典定义,非常适合研究这些局限性,并强调当前NLP系统自动评估中的问题是如何具体阻碍这项研究的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Dictionaries
Dictionaries Arts and Humanities-Language and Linguistics
CiteScore
0.80
自引率
0.00%
发文量
12
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