Learning concept abstractness using weak supervision

Ella Rabinovich; Benjamin Sznajder; Artem Spector; Ilya Shnayderman; Ranit Aharonov; David Konopnicki; Noam Slonim

Learning concept abstractness using weak supervision

Ella Rabinovich, Benjamin Sznajder, Artem Spector, Ilya Shnayderman, Ranit Aharonov, David Konopnicki, Noam Slonim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data. Exploiting only minimal linguistic clues and the contextual usage of a concept as manifested in textual data, we train sufficiently powerful classifiers, obtaining high correlation with human labels. The results imply the applicability of this approach to additional properties of concepts, additional languages, and resource-scarce scenarios.

Original language	English
Title of host publication	Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
Editors	Ellen Riloff, David Chiang, Julia Hockenmaier, Jun'ichi Tsujii
Publisher	Association for Computational Linguistics
Pages	4854-4859
Number of pages	6
ISBN (Electronic)	9781948087841
State	Published - 2018
Externally published	Yes
Event	2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 - Brussels, Belgium Duration: 31 Oct 2018 → 4 Nov 2018

Publication series

Name	Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

Conference

Conference	2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
Country/Territory	Belgium
City	Brussels
Period	31/10/18 → 4/11/18

Bibliographical note

Publisher Copyright:
© 2018 Association for Computational Linguistics

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Information Systems

Cite this

Rabinovich, E., Sznajder, B., Spector, A., Shnayderman, I., Aharonov, R., Konopnicki, D., & Slonim, N. (2018). Learning concept abstractness using weak supervision. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 (pp. 4854-4859). (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018). Association for Computational Linguistics.

Rabinovich, Ella ; Sznajder, Benjamin ; Spector, Artem et al. / Learning concept abstractness using weak supervision. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. editor / Ellen Riloff ; David Chiang ; Julia Hockenmaier ; Jun'ichi Tsujii. Association for Computational Linguistics, 2018. pp. 4854-4859 (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

@inproceedings{8452d08e326545b1b4daecbd9578a714,

title = "Learning concept abstractness using weak supervision",

abstract = "We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data. Exploiting only minimal linguistic clues and the contextual usage of a concept as manifested in textual data, we train sufficiently powerful classifiers, obtaining high correlation with human labels. The results imply the applicability of this approach to additional properties of concepts, additional languages, and resource-scarce scenarios.",

author = "Ella Rabinovich and Benjamin Sznajder and Artem Spector and Ilya Shnayderman and Ranit Aharonov and David Konopnicki and Noam Slonim",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics; 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 ; Conference date: 31-10-2018 Through 04-11-2018",

year = "2018",

language = "English",

series = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018",

publisher = "Association for Computational Linguistics",

pages = "4854--4859",

editor = "Ellen Riloff and David Chiang and Julia Hockenmaier and Jun'ichi Tsujii",

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Rabinovich, E, Sznajder, B, Spector, A, Shnayderman, I, Aharonov, R, Konopnicki, D & Slonim, N 2018, Learning concept abstractness using weak supervision. in E Riloff, D Chiang, J Hockenmaier & J Tsujii (eds), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, Association for Computational Linguistics, pp. 4854-4859, 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, Brussels, Belgium, 31/10/18.

Learning concept abstractness using weak supervision. / Rabinovich, Ella; Sznajder, Benjamin; Spector, Artem et al.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. ed. / Ellen Riloff; David Chiang; Julia Hockenmaier; Jun'ichi Tsujii. Association for Computational Linguistics, 2018. p. 4854-4859 (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sznajder, Benjamin

AU - Spector, Artem

AU - Shnayderman, Ilya

AU - Aharonov, Ranit

AU - Konopnicki, David

AU - Slonim, Noam

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AB - We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data. Exploiting only minimal linguistic clues and the contextual usage of a concept as manifested in textual data, we train sufficiently powerful classifiers, obtaining high correlation with human labels. The results imply the applicability of this approach to additional properties of concepts, additional languages, and resource-scarce scenarios.

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M3 - Conference contribution

AN - SCOPUS:85081726892

T3 - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

SP - 4854

EP - 4859

BT - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

A2 - Riloff, Ellen

A2 - Chiang, David

A2 - Hockenmaier, Julia

A2 - Tsujii, Jun'ichi

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Y2 - 31 October 2018 through 4 November 2018

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Rabinovich E, Sznajder B, Spector A, Shnayderman I, Aharonov R, Konopnicki D et al. Learning concept abstractness using weak supervision. In Riloff E, Chiang D, Hockenmaier J, Tsujii J, editors, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Association for Computational Linguistics. 2018. p. 4854-4859. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Learning concept abstractness using weak supervision

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ASJC Scopus subject areas

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