Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings

• URL: http://arxiv.org/abs/2205.13858v1
• Date: Fri, 27 May 2022 09:40:33 GMT
• Title: Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings
• Authors: Timothee Mickus and Kees van Deemter and Mathieu Constant and Denis Paperno
• Abstract summary: We focus on relating opaque word vectors with human-readable definitions. This problem naturally divides into two subtasks: converting definitions into embeddings, and converting embeddings into definitions. This task was conducted in a multilingual setting, using comparable sets of embeddings trained homogeneously.
• Score: 1.5293427903448025
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Word embeddings have advanced the state of the art in NLP across numerous tasks. Understanding the contents of dense neural representations is of utmost interest to the computational semantics community. We propose to focus on relating these opaque word vectors with human-readable definitions, as found in dictionaries. This problem naturally divides into two subtasks: converting definitions into embeddings, and converting embeddings into definitions. This task was conducted in a multilingual setting, using comparable sets of embeddings trained homogeneously.

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