词义链接：越过沙盒进行消歧义

摘要

词义消歧（WSD）是将给定上下文中的单词与一组可能的候选含义中的最合适含义关联的任务。尽管最近这一任务再次引起了人们的兴趣，系统的性能已经超过了估计的标注者间一致性，但在撰写本文时，该任务仍然难以找到下游应用。我们认为导致这一困难的原因之一是将WSD应用于纯文本的困难。事实上，在标准的表述中，模型工作的假设是a）所有需要消歧的跨度已经被识别出来，以及b）每个跨度的所有可能候选含义都已提供，这两者都是远非微不足道的要求。在这项工作中，我们提出了一个名为词义链接（WSL）的新任务，在给定输入文本和参考含义库的情况下，系统必须同时识别要消歧的跨度，并将它们链接到最合适的含义。我们提出了一个基于Transformer架构的任务，并对其性能以及针对WSL进行缩放的最先进WSD系统的性能进行了彻底评估，逐步放宽了WSD的假设。我们希望我们的工作将促进词汇语义更容易地整合到下游应用中。

English

Word Sense Disambiguation (WSD) is the task of associating a word in a given context with its most suitable meaning among a set of possible candidates. While the task has recently witnessed renewed interest, with systems achieving performances above the estimated inter-annotator agreement, at the time of writing it still struggles to find downstream applications. We argue that one of the reasons behind this is the difficulty of applying WSD to plain text. Indeed, in the standard formulation, models work under the assumptions that a) all the spans to disambiguate have already been identified, and b) all the possible candidate senses of each span are provided, both of which are requirements that are far from trivial. In this work, we present a new task called Word Sense Linking (WSL) where, given an input text and a reference sense inventory, systems have to both identify which spans to disambiguate and then link them to their most suitable meaning.We put forward a transformer-based architecture for the task and thoroughly evaluate both its performance and those of state-of-the-art WSD systems scaled to WSL, iteratively relaxing the assumptions of WSD. We hope that our work will foster easier integration of lexical semantics into downstream applications.

词义链接：越过沙盒进行消歧义

Word Sense Linking: Disambiguating Outside the Sandbox

摘要

Summary

Support