Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association

This paper describes the system submitted to SemEval 2018 shared task 10 {`}Capturing Dicriminative Attributes{'}. We use a combination of knowledge-based and co-occurrence features to capture the semantic difference between two words in relation to an attribute. We define scores based on association measures, ngram counts, word similarity, and ConceptNet relations. The system is ranked 4th (joint) on the official leaderboard of the task.

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here