Jack the Reader – A Machine Reading Framework
Dirk Weissenborn, Pasquale Minervini, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bošnjak, Jeff Mitchell, Thomas Demeester, Tim Dettmers, Pontus Stenetorp, Sebastian Riedel
Abstract
Many Machine Reading and Natural Language Understanding tasks require reading supporting text in order to answer questions. For example, in Question Answering, the supporting text can be newswire or Wikipedia articles; in Natural Language Inference, premises can be seen as the supporting text and hypotheses as questions. Providing a set of useful primitives operating in a single framework of related tasks would allow for expressive modelling, and easier model comparison and replication. To that end, we present Jack the Reader (JACK), a framework for Machine Reading that allows for quick model prototyping by component reuse, evaluation of new models on existing datasets as well as integrating new datasets and applying them on a growing set of implemented baseline models. JACK is currently supporting (but not limited to) three tasks: Question Answering, Natural Language Inference, and Link Prediction. It is developed with the aim of increasing research efficiency and code reuse.- Anthology ID:
- P18-4005
- Volume:
- Proceedings of ACL 2018, System Demonstrations
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Fei Liu, Thamar Solorio
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 25–30
- Language:
- URL:
- https://aclanthology.org/P18-4005
- DOI:
- 10.18653/v1/P18-4005
- Cite (ACL):
- Dirk Weissenborn, Pasquale Minervini, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bošnjak, Jeff Mitchell, Thomas Demeester, Tim Dettmers, Pontus Stenetorp, and Sebastian Riedel. 2018. Jack the Reader – A Machine Reading Framework. In Proceedings of ACL 2018, System Demonstrations, pages 25–30, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Jack the Reader – A Machine Reading Framework (Weissenborn et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/P18-4005.pdf
- Code
- uclmr/jack
- Data
- FB15k-237, MultiNLI, NewsQA, SNLI, SQuAD, TriviaQA