TiFi: Taxonomy Induction for Fictional Domains[Extended version]
Table 2. Step 1 - In-domain category cleaning.
['[BOLD] Method', '[BOLD] Universe', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1-score']
Furthermore, we combine both methods into a joint filter. TiFi achieves both superior precision (+40%) and F1-score (+22%/+23%), while observing a smaller drop in recall (-18%/-15%). On both fully annotated universes the improvement of TiFi over the combined baseline in terms of F1-score is statistically significant (p-value 2.2−16 and 1.9−13, respectively). The considerable difference in precision is explained largely by the limited coverage of the rule-based baseline. Typical errors TiFi still makes are cases where categories have the potential to be relevant, yet appear to have no instances, e.g., song in LOTR. Also, it occasionally misses out on conceptual categories which do not have plural forms, e.g., Food.