Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity systems

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S14-2072.pdf (260.13 KB)

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https://aclanthology.org/S14-2072/

Permanent Link

http://hdl.handle.net/11603/11834
 http://dx.doi.org/10.3115/v1/S14-2072

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UMBC Computer Science and Electrical Engineering Department
UMBC Faculty Collection
UMBC Student Collection

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Author/Creator ORCID

https://orcid.org/0000-0002-2624-6223
 https://orcid.org/0000-0002-9311-954X
 https://orcid.org/0000-0002-6593-1792

Date

2014-08-23

Type of Work

conference papers and proceedings
Text

Department

Program

Citation of Original Publication

Abhay Kashyap, Lushan Han, Roberto Yus, Jennifer Sleeman, Taneeya Satyapanich, Sunil Gandhi, and Tim Finin. 2014. Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity Systems. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pages 416–423, Dublin, Ireland. Association for Computational Linguistics. http://dx.doi.org/10.3115/v1/S14-2072

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Attribution 4.0 International (CC BY 4.0)
https://creativecommons.org/licenses/by/4.0/

Subjects

human language technology
lexical semantics
natural language processing
semantics
UMBC Ebiquity Research Group

Abstract

We describe UMBC's systems developed for the SemEval 2014 tasks on Multilingual Semantic Textual Similarity (Task 10) and Cross-Level Semantic Similarity (Task 3). Our best submission in the Multilingual task ranked second in both English and Spanish subtasks using an unsupervised approach. Our best systems for Cross-Level task ranked second in Paragraph-Sentence and first in both Sentence-Phrase and Word-Sense subtask. The system ranked first for the Phrase- Word subtask but was not included in the official results due to a late submission.