GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns
Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, Francesca Toni
Abstract
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 algorithm, as well as domain-specific custom attributes which can be incorporated into the library by implementing two functions. The library is equipped with a web-based interface empowering human users to conveniently explore data via the extracted patterns, using complementary pattern-centric and example-centric views: the former includes a reading in natural language and statistics of each extracted pattern; the latter shows applications of each extracted pattern to training examples. We demonstrate the usefulness of the library in classification (spam detection and argument mining), model analysis (machine translation), and artifact discovery in datasets (SNLI and 20Newsgroups).- Anthology ID:
- 2022.lrec-1.655
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6093–6103
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.655
- DOI:
- Cite (ACL):
- Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, and Francesca Toni. 2022. GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6093–6103, Marseille, France. European Language Resources Association.
- Cite (Informal):
- GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns (Lertvittayakumjorn et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2022.lrec-1.655.pdf
- Code
- plkumjorn/GrASP
- Data
- SNLI