Chinese Named Entity Recognition Augmented with Lexicon Memory
Table 6: Results on the OntoNotes-4 dataset
['[BOLD] Model', '[BOLD] P (%)', '[BOLD] R (%)', '[BOLD] F1 (%)']
The LEMON-2 achieved state-of-the-art results on all the four datasets. Our model also achieved the highest F1-score Note that the Weibo NER data is extracted from the social media, it is full of non-standard expressions and only contains about 1.4k samples. The problems of out-of-vocabulary words and ambiguity of word boundaries become more serious for NER on this dataset.