Multilingual Information Extraction with PolyglotIE

Alan Akbik, Laura Chiticariu, Marina Danilevsky, Yonas Kbrom, Yunyao Li, Huaiyu Zhu

Abstract
We present PolyglotIE, a web-based tool for developing extractors that perform Information Extraction (IE) over multilingual data. Our tool has two core features: First, it allows users to develop extractors against a unified abstraction that is shared across a large set of natural languages. This means that an extractor needs only be created once for one language, but will then run on multilingual data without any additional effort or language-specific knowledge on part of the user. Second, it embeds this abstraction as a set of views within a declarative IE system, allowing users to quickly create extractors using a mature IE query language. We present PolyglotIE as a hands-on demo in which users can experiment with creating extractors, execute them on multilingual text and inspect extraction results. Using the UI, we discuss the challenges and potential of using unified, crosslingual semantic abstractions as basis for downstream applications. We demonstrate multilingual IE for 9 languages from 4 different language groups: English, German, French, Spanish, Japanese, Chinese, Arabic, Russian and Hindi.
Anthology ID:
C16-2056
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
Month:
December
Year:
2016
Address:
Osaka, Japan
Editor:
Hideo Watanabe
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
268–272
Language:
URL:
https://aclanthology.org/C16-2056
DOI:
Bibkey:
Cite (ACL):
Alan Akbik, Laura Chiticariu, Marina Danilevsky, Yonas Kbrom, Yunyao Li, and Huaiyu Zhu. 2016. Multilingual Information Extraction with PolyglotIE. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 268–272, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Multilingual Information Extraction with PolyglotIE (Akbik et al., COLING 2016)
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