Year: 2020
Type: conference-paper
Abstract: In this paper, we present a rule-based sentence boundary disambiguation Python package that works out-of-the-box for 22 languages.We aim to provide a realistic segmenter which can provide logical sentences even when the format and domain of the input text is unknown.In our work, we adapt the Golden Rules Set (a language specific set of sentence boundary exemplars) originally implemented as a ruby gem pragmatic segmenter 1 which we ported to Python with additional improvements and functionality.PySBD passes 97.92% of the Golden Rule Set examplars for English, an improvement of 25% over the next best open source Python tool.
Authors: Nipun Sadvilkar, Mark Neumann
Institution: Allen Institute for Artificial Intelligence
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W3092892072