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RAW-C: Relatedness of Ambiguous Words in Context (A New Lexical Resource for English) ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Bergen, Benjamin
;
Trott, Sean
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.acl-long.550 Abstract: Most words are ambiguous––i.e., they convey distinct meanings in different contexts––and even the meanings of unambiguous words are context-dependent. Both phenomena present a challenge for NLP. Recently, the advent of contextualized word embeddings has led to success on tasks involving lexical ambiguity, such as Word Sense Disambiguation. However, there are few tasks that directly evaluate how well these contextualized embeddings accommodate the more continuous, dynamic nature of word meaning––particularly in a way that matches human intuitions. We introduce RAW-C, a dataset of graded, human relatedness judgments for 112 ambiguous words in context (with 672 sentence pairs total), as well as human estimates of sense dominance. The average inter-annotator agreement (assessed using a leave-one-annotator-out method) was 0.79. We then show that a measure of cosine distance, computed using contextualized embeddings from BERT and ELMo, correlates ...
Keyword:
Computational Linguistics
;
Condensed Matter Physics
;
Deep Learning
;
Electromagnetism
;
FOS Physical sciences
;
Information and Knowledge Engineering
;
Neural Network
;
Semantics
URL:
https://dx.doi.org/10.48448/fc6y-2r22
https://underline.io/lecture/25785-raw-c-relatedness-of-ambiguous-words-in-context-(a-new-lexical-resource-for-english)
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