Entity Linking for Queries by Searching Wikipedia Sentences
Table 4: Results on the ERD dataset. Results of the baseline systems are taken from Table 8 in Cornolti et al. (2016) and reported by the ERD organizer (Carmel et al., 2014). We only report the F1 score as precision and recall are not reported in previous work. *Significant improvement over state-of-the-art baselines (t-test, p < 0.05).
['System', '[ITALIC] Pavg', '[ITALIC] Ravg', '[ITALIC] F1 [ITALIC] avg']
On the ERD14 dataset, WAT is superior to AIDA but it is still up to 10% than SMAPH-1 that wins the ERD Challenge. SMAPH-2 improves 2% than SMAPH-1. Our system significantly outperforms the state-of-the-art annotator SMAPH-2 by 4.2%. On the GERDAQ dataset, our system is 2.5% superior to the state-of-the-art annotator SMAPH-2. The F1 score in this dataset is much lower than the ERD dataset because common concepts such as “Week” and “Game” that are not annotated in the ERD dataset are annotated in the GERDAQ dataset.