Pairwise Representation Learning for Event Coreference

Understand

Natural Language Processing tasks such as resolving the coreference of events require understanding the relations between two text snippets.

• These tasks are typically formulated as (binary) classification problems over independently induced representations of the text snippets.
• In this work, we develop a Pairwise Representation Learning (PairwiseRL) scheme for the event mention pairs, in which we jointly encode a pair of text snippets so that the representation of each mention in the pair is induced in the context of the other one.
• Furthermore, our representation supports a finer, structured representation of the text snippet to facilitate encoding events and their arguments.