MineriaUNAM at SemEval-2020 Task 3: Predicting Contextual WordSimilarity Using a Centroid Based Approach and Word Embeddings
24644Authors
nan
Abstract
AbstractThis paper presents our systems to solve Task 3 of Semeval-2020, which aims to predict the effect that context has on human perception of similarity of words. The task consists of two subtasks in English, Croatian, Finnish, and Slovenian: (1) predicting the change of similarity and (2) predicting the human scores of similarity, both of them for a pair of words within two different contexts. We tackled the problem by developing two systems, the first one uses a centroid approach and word vectors. The second one uses the ELMo language model, which is trained for each pair of words with the given context. Our approach achieved the highest score in subtask 2 for the English language.
Keywords
Full Content
nan
Labeled Text
AbstractThis paper presents our systems to solve Task 3 of Semeval-2020, which aims to predict the effect that context has on human perception of similarity of words. The task consists of two subtasks in English, Croatian, Finnish, and Slovenian: (1) predicting the change of similarity and (2) predicting the human scores of similarity, both of them for a pair of words within two different contexts. We tackled the problem by developing two systems, the first one uses a centroid approach and word vectors. The second one uses the ELMo language model, which is trained for each pair of words with the given context. Our approach achieved the highest score in subtask 2 for the English language.
Publication Details
- Paper ID:
- 24644
- Year:
- 2020
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan