Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations

Anonymous

Paper Link: https://openreview.net/forum?id=viX7312zHYb

Paper Type: Short paper (up to four pages of content + unlimited references and appendices)

Abstract:

NLP models that process multiple texts often struggle in recognizing corresponding and salient information that is often differently phrased, and consolidating the redundancies across texts.
To facilitate research of such challenges, the sentence fusion task was proposed, yet previous datasets for this task were very limited in their size and scope. In this paper, we revisit and substantially extend previous dataset creation efforts. With careful modifications, relabeling, and employing complementing data sources, we were able to more than triple the size of a notable earlier dataset.
Moreover, we show that our extended version uses more representative texts for multi-document tasks and provides a more diverse training set, which substantially improves model performance.

Presentation Mode: This paper will be presented in person in Seattle

Copyright Consent Signature (type Name Or NA If Not Transferrable): Paul Roit

Copyright Consent Name And Address: Bar-Ilan University, Ramat-Gan, Israel