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

Understand

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.