Knowledge-Augmented Language Model and Its Application to Unsupervised Named-Entity Recognition
Table 3: Language modeling results on the recipe and CoNLL 2003 datasets
['[EMPTY]', 'model', 'unidirectional validation', 'unidirectional test', 'bidirectional validation', 'bidirectional test']
The improvement relative to NE-LM is larger in the unidirectional setting compared to the bidirectional setting. We conjecture that this is because in that setting NE-LM trains a bidirectional NER in a supervised way. The improvement relative to NE-LM is larger on CoNLL 2003 than on the recipe dataset. We believe that the inference heuristic used by NE-LM is tuned specifically to recipes and is less suitable to the CoNLL setting.