Papers › EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery

EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery

1 Jun 2018SEMEVAL 2018 6archive 2025-07-28

Ahmad Issa Alaa Aldine, Mounira Harzallah, Giuseppe Berio, Nicolas B{\'e}chet, Ahmad Faour

In this paper, we present our proposed system (EXPR) to participate in the hypernym discovery task of SemEval 2018. The task addresses the challenge of discovering hypernym relations from a text corpus. Our proposal is a combined approach of path-based technique and distributional technique. We use dependency parser on a corpus to extract candidate hypernyms and represent their dependency paths as a feature vector. The feature vector is concatenated with a feature vector obtained using Wikipedia pre-trained term embedding model. The concatenated feature vector fits a supervised machine learning method to learn a classifier model. This model is able to classify new candidate hypernyms as hypernym or not. Our system performs well to discover new hypernyms not defined in gold hypernyms.

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Tasks

Hypernym DiscoveryInformation RetrievalMachine TranslationQuestion Answering

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Hypernym Discovery Medical domain EXPR MAP 13.77 #5 of 8 Archive leaderboard report
Hypernym Discovery Medical domain EXPR MRR 40.76 #5 of 8 Archive leaderboard report
Hypernym Discovery Medical domain EXPR P@5 12.76 #5 of 8 Archive leaderboard report

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