Event Extraction for Portuguese: A QA-driven Approach using ACE-2005
This work addresses the lack of event extraction resources for Portuguese, providing a new annotated corpus and benchmark, but it is incremental as it adapts existing methods to a new language.
The paper tackles event extraction for Portuguese by proposing a BERT-based framework that decomposes the task into trigger detection and argument classification via question answering, achieving F1 scores of 64.4 for trigger classification and 46.7 for argument classification, setting a new state-of-the-art for Portuguese.
Event extraction is an Information Retrieval task that commonly consists of identifying the central word for the event (trigger) and the event's arguments. This task has been extensively studied for English but lags behind for Portuguese, partly due to the lack of task-specific annotated corpora. This paper proposes a framework in which two separated BERT-based models were fine-tuned to identify and classify events in Portuguese documents. We decompose this task into two sub-tasks. Firstly, we use a token classification model to detect event triggers. To extract event arguments, we train a Question Answering model that queries the triggers about their corresponding event argument roles. Given the lack of event annotated corpora in Portuguese, we translated the original version of the ACE-2005 dataset (a reference in the field) into Portuguese, producing a new corpus for Portuguese event extraction. To accomplish this, we developed an automatic translation pipeline. Our framework obtains F1 marks of 64.4 for trigger classification and 46.7 for argument classification setting, thus a new state-of-the-art reference for these tasks in Portuguese.