Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings
Timothee Mickus, Kees van Deemter, Mathieu Constant, Denis Paperno
2022Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)19 citationsDOIOpen Access PDF
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.
Topics & Concepts
Computer scienceSemEvalWord (group theory)Task (project management)Focus (optics)Natural language processingArtificial intelligenceSemantics (computer science)LinguisticsProgramming languageOpticsEconomicsPhilosophyManagementPhysicsNatural Language Processing TechniquesTopic ModelingText Readability and Simplification