What Matters for Neural Cross-Lingual Named Entity Recognition: An Empirical Analysis
Table 6: OOV rate (percentage) in our bilingual word embeddings across the four languages. Type indicates unique words, and token refers to counting token numbers.
['Language', 'Type', 'Token']
The colloquium words from social media may cause the issue of out of vocabulary (OOV) and further impact the transferring process. The OOV rate of Bengali is significantly higher than that of the other three languages. This suggests that the high OOV rate and the discrepancy of data sources may hurt the effectiveness of transfer.