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Financial Event Extraction Using Wikipedia-Based Weak Supervision

25 November 2019
L. Ein-Dor
Ariel Gera
Orith Toledo-Ronen
Alon Halfon
Benjamin Sznajder
Lena Dankin
Yonatan Bilu
Yoav Katz
Noam Slonim
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Abstract

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.

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