Scientific Information Extraction with Semi-supervised Neural Tagging
Table 3: F1 score on the dev and test sets for using different sources of data for pretraining.
['Initialization', 'Dev MS', 'Dev Phy', 'Dev CS', 'Test MS', 'Test Phy', 'Test CS']
We explore different word embedding pre-training with ScienceIE training set alone (SE), and adding other external resources including Wikipedia (wiki) and Computer Science articles (ACM). All alternatives use word2vec. Compared with using SE alone, introduction of all external data sources improve performance. Moreover, we observe that with the introduction of the ACM dataset, the performance on the CS domain is increased significantly in both the dev and test sets. Adding Wikipedia data benefits all three domains, with more significant improvement on the MS and Physics domains.