Abstract
In this paper, we present kogito, an open-source tool for generating commonsense inferences about situations described in text. kogito provides an intuitive and extensible interface to interact with natural language generation models that can be used for hypothesizing commonsense knowledge inference from a textual input. In particular, kogito offers several features for targeted, multi-granularity knowledge generation. These include a standardized API for training and evaluating knowledge models, and generating and filtering inferences from them. We also include helper functions for converting natural language texts into a format ingestible by knowledge models — intermediate pipeline stages such as knowledge head extraction from text, heuristic and model-based knowledge head-relation matching, and an ability to define and use custom knowledge relations. We make the code for kogito available at https://github.com/epfl-nlp/kogito along with thorough documentation at https://kogito.readthedocs.io.- Anthology ID:
- 2023.eacl-demo.12
- Volume:
- Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Danilo Croce, Luca Soldaini
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 96–104
- Language:
- URL:
- https://aclanthology.org/2023.eacl-demo.12
- DOI:
- 10.18653/v1/2023.eacl-demo.12
- Cite (ACL):
- Mete Ismayilzada and Antoine Bosselut. 2023. kogito: A Commonsense Knowledge Inference Toolkit. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 96–104, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- kogito: A Commonsense Knowledge Inference Toolkit (Ismayilzada & Bosselut, EACL 2023)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/2023.eacl-demo.12.pdf