PROTEST-ER: Retraining BERT for Protest Event Extraction
2021-08-01ACL (CASE) 2021Unverified0· sign in to hype
Tommaso Caselli, Osman Mutlu, Angelo Basile, Ali Hürriyetoğlu
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ReproduceAbstract
We analyze the effect of further retraining BERT with different domain specific data as an unsupervised domain adaptation strategy for event extraction. Portability of event extraction models is particularly challenging, with large performance drops affecting data on the same text genres (e.g., news). We present PROTEST-ER, a retrained BERT model for protest event extraction. PROTEST-ER outperforms a corresponding generic BERT on out-of-domain data of 8.1 points. Our best performing models reach 51.91-46.39 F1 across both domains.