GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. (arXiv:2104.03958v2 [cs.CL] UPDATED)

Web: http://arxiv.org/abs/2104.03958

Data exploration is an important step of every data science and machine
learning project, including those involving textual data. We provide a novel
language tool, in the form of a publicly available Python library for
extracting patterns from textual data. The library integrates a first public
implementation of the existing GrASP algorithm. It allows users to extract
patterns using a number of general-purpose built-in linguistic attributes (such
as hypernyms, part-of-speech tags, and syntactic dependency tags), as envisaged
for the original …

arxiv human library patterns