The Grid: A semi-automated tool to support expert-driven modeling
Allegra A. Beal Cohen, Maria Alexeeva, Keith Alcock, Mihai Surdeanu
Abstract
When building models of human behavior, we often struggle to find data that capture important factors at the right level of granularity. In these cases, we must rely on expert knowledge to build models. To help partially automate the organization of expert knowledge for modeling, we combine natural language processing (NLP) and machine learning (ML) methods in a tool called the Grid. The Grid helps users organize textual knowledge into clickable cells aLong two dimensions using iterative, collaborative clustering. We conduct a user study to explore participants’ reactions to the Grid, as well as to investigate whether its clustering feature helps participants organize a corpus of expert knowledge. We find that participants using the Grid’s clustering feature appeared to work more efficiently than those without it, but written feedback about the clustering was critical. We conclude that the general design of the Grid was positively received and that some of the user challenges can likely be mitigated through the use of LLMs.- Anthology ID:
- 2024.nlp4science-1.19
- Volume:
- Proceedings of the 1st Workshop on NLP for Science (NLP4Science)
- Month:
- November
- Year:
- 2024
- Address:
- Miami, FL, USA
- Editors:
- Lotem Peled-Cohen, Nitay Calderon, Shir Lissak, Roi Reichart
- Venue:
- NLP4Science
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 219–229
- Language:
- URL:
- https://aclanthology.org/2024.nlp4science-1.19
- DOI:
- 10.18653/v1/2024.nlp4science-1.19
- Cite (ACL):
- Allegra A. Beal Cohen, Maria Alexeeva, Keith Alcock, and Mihai Surdeanu. 2024. The Grid: A semi-automated tool to support expert-driven modeling. In Proceedings of the 1st Workshop on NLP for Science (NLP4Science), pages 219–229, Miami, FL, USA. Association for Computational Linguistics.
- Cite (Informal):
- The Grid: A semi-automated tool to support expert-driven modeling (A. Beal Cohen et al., NLP4Science 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.nlp4science-1.19.pdf