Enriching Word Vectors with Subword Information
Table 2: Accuracy of our model and baselines on word analogy tasks for Czech, German, English and Italian. We report results for semantic and syntactic analogies separately.
['Cs', 'Semantic', 'sg 25.7', 'cbow 27.6', 'sisg 27.5']
We observe that morphological information significantly improves the syntactic tasks; our approach outperforms the baselines. In contrast, it does not help for semantic questions, and even degrades the performance for German and Italian. Note that this is tightly related to the choice of the length of character n-grams that we consider. We show in Sec. Another interesting observation is that, as expected, the improvement over the baselines is more important for morphologically rich languages, such as Czech and German.