Financial Event Extraction Using Wikipedia-Based Weak Supervision
Table 4: Model performance for identifying 26 Wikipedia events in the news data.
['Model', 'Recall', 'Avg. Rank']
This may be due to the difference in writing style between the two sources. Notably, even though SentiFM-binary was trained on news data, its recall is the lowest among the three models. This may be attributed to the mismatch between the event types in SentiFM and those in Wikipedia. Clearly, the Wikipedia reference events do not fully cover all company-related events that occurred over this time period. Still, since we presume events mentioned in Wikipedia are relatively significant, we expect a good event-detection model to rank them among its top predictions.