PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search. (arXiv:2207.09068v3 [cs.CL] UPDATED)

Since BERT (Devlin et al., 2018), learning contextualized word embeddings has
been a de-facto standard in NLP. However, the progress of learning
contextualized phrase embeddings is hindered by the lack of a human-annotated,
phrase-in-context benchmark. To fill this gap, we propose PiC - a dataset of
~28K of noun phrases accompanied by their contextual Wikipedia pages and a
suite of three tasks of increasing difficulty for evaluating the quality of
phrase embeddings. We find that training on our dataset improves …

arxiv context dataset search semantic understanding