Abstract
Supervised distributional methods are applied successfully in lexical entailment, but recent work questioned whether these methods actually learn a relation between two words. Specifically, Levy et al. (2015) claimed that linear classifiers learn only separate properties of each word. We suggest a cheap and easy way to boost the performance of these methods by integrating multiplicative features into commonly used representations. We provide an extensive evaluation with different classifiers and evaluation setups, and suggest a suitable evaluation setup for the task, eliminating biases existing in previous ones.
Original language | English |
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Title of host publication | NAACL HLT 2018 - Lexical and Computational Semantics, SEM 2018, Proceedings of the 7th Conference |
Editors | Malvina Nissim, Jonathan Berant, Alessandro Lenci |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 160-166 |
Number of pages | 7 |
ISBN (Electronic) | 9781948087223 |
DOIs | |
State | Published - 2018 |
Event | 7th Joint Conference on Lexical and Computational Semantics, SEM 2018, co-located with NAACL HLT 2018 - New Orleans, United States Duration: 5 Jun 2018 → 6 Jun 2018 |
Publication series
Name | NAACL HLT 2018 - Lexical and Computational Semantics, SEM 2018, Proceedings of the 7th Conference |
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Conference
Conference | 7th Joint Conference on Lexical and Computational Semantics, SEM 2018, co-located with NAACL HLT 2018 |
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Country/Territory | United States |
City | New Orleans |
Period | 5/06/18 → 6/06/18 |
Bibliographical note
Publisher Copyright:© 2018 Association for Computational Linguistics.
Funding
Vered is supported in part by an Intel ICRI-CI grant, the Israel Science Foundation grant 1951/17, the German Research Foundation through the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1), the Clore Scholars Pro-gramme (2017), and the AI2 Key Scientific Challenges Program (2017). Vered is supported in part by an Intel ICRI-CI grant, the Israel Science Foundation grant 1951/17, the German Research Foundation through the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1), the Clore Scholars Programme (2017), and the AI2 Key Scientific Challenges Program (2017).
Funders | Funder number |
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AI2 Key Scientific Challenges Program | |
Clore Scholars Pro-gramme | |
DIP | DA 1600/1-1 |
German-Israeli Project Cooperation | |
Intel ICRI-CI | |
Deutsche Forschungsgemeinschaft | |
Israel Science Foundation | 1951/17 |