Abstract
Semantic applications typically extract in-formation from intermediate structures de-rived from sentences, such as dependency parse or semantic role labeling. In this pa-per, we study Open Information Extrac-tion's (Open IE) output as an additional in-termediate structure and find that for tasks such as text comprehension, word similar-ity and word analogy it can be very effec-tive. Specifically, for word analogy, Open IE-based embeddings surpass the state of the art. We suggest that semantic applica-tions will likely benefit from adding Open IE format to their set of potential sentence-level structures.
Original language | English |
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Title of host publication | ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 303-308 |
Number of pages | 6 |
ISBN (Electronic) | 9781941643730 |
DOIs | |
State | Published - 2015 |
Event | 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 - Beijing, China Duration: 26 Jul 2015 → 31 Jul 2015 |
Publication series
Name | ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference |
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Volume | 2 |
Conference
Conference | 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 |
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Country/Territory | China |
City | Beijing |
Period | 26/07/15 → 31/07/15 |
Bibliographical note
Publisher Copyright:© 2015 Association for Computational Linguistics.