Financial Event Extraction Using Wikipedia-Based Weak Supervision

TL;DR

This paper introduces a weak supervision method for extracting financial and economic events from text using Wikipedia, eliminating the need for extensive knowledge bases and enabling the extraction of events related to unseen companies.

Contribution

The approach leverages Wikipedia sections for weak labels, removing the dependency on existing event knowledge bases or financial figures, and generalizes to unseen companies.

Findings

Effective extraction of economic events without prior event knowledge.

No requirement for external financial figures or knowledge bases.

Applicable to companies not present in training data.

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.