Financial Event Extraction Using Wikipedia-Based Weak Supervision

Extraction of financial and economic events from text has previously been done mostly using rule-based methods, with more recent works employing machine learning techniques. This work is in line with this latter approach, leveraging relevant Wikipedia sections to extract weak labels for sentences de...

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Bibliographic Details
Main Authors Ein-Dor, Liat, Gera, Ariel, Toledo-Ronen, Orith, Halfon, Alon, Sznajder, Benjamin, Dankin, Lena, Bilu, Yonatan, Katz, Yoav, Slonim, Noam
Format Journal Article
LanguageEnglish
Published 25.11.2019
Subjects
Computer Science - Computation and Language
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Summary:Extraction of financial and economic events from text has previously been done mostly using rule-based methods, with more recent works employing machine learning techniques. This work is in line with this latter approach, leveraging relevant Wikipedia sections to extract weak labels for sentences describing economic events. Whereas previous weakly supervised approaches required a knowledge-base of such events, or corresponding financial figures, our approach requires no such additional data, and can be employed to extract economic events related to companies which are not even mentioned in the training data.
DOI:10.48550/arxiv.1911.10783