Multi-Word Lexical Simplification

Piotr Przybyła; Matthew Shardlow

COLING 2020main11 citations

Multi-Word Lexical Simplification

Abstract

In this work we propose the task of multi-word lexical simplification, in which a sentence in natural language is made easier to understand by replacing its fragment with a simpler alternative, both of which can consist of many words. In order to explore this new direction, we contribute a corpus (MWLS1), including 1462 sentences in English from various sources with 7059 simplifications provided by human annotators. We also propose an automatic solution (Plainifier) based on a purpose-trained neural language model and evaluate its performance, comparing to human and resource-based baselines.

BibTeX

@inproceedings{przybyla-shardlow-2020-multi,
    title = "Multi-Word Lexical Simplification",
    author = "Przyby{\l}a, Piotr  and
      Shardlow, Matthew",
    editor = "Scott, Donia  and
      Bel, Nuria  and
      Zong, Chengqing",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.123/",
    doi = "10.18653/v1/2020.coling-main.123",
    pages = "1435--1446"
}