Learning Relational Dependency Networks for Relation Extraction
Table 7: word2vec Results comparing models trained without (-w2v) and with word2vec features (+w2v).
['Relation', 'AUC ROC -w2v', 'AUC ROC +w2v']
word2vec appears to largely have no impact, boosting results in just 4 relations. We hypothesize that this may be due to a limitation in the depth of trees learned. Learning more and/or deeper trees may improve use of word2vec features, and additional work can be done to generate deep features from word vectors. Q3 is answered cautiously in the negative, although future work could lead to improvements.