Polyglot: Distributed Word Representations for Multilingual NLP

Understand

Distributed word representations (word embeddings) have recently contributed to competitive performance in language modeling and several NLP tasks.

• In this work, we train word embeddings for more than 100 languages using their corresponding Wikipedias.
• We quantitatively demonstrate the utility of our word embeddings by using them as the sole features for training a part of speech tagger for a subset of these languages.
• We find their performance to be competitive with near state-of-art methods in English, Danish and Swedish.