Jack the Reader - A Machine Reading Framework
June 20, 2018 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
"No code URL or promise found in abstract"
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Authors
Dirk Weissenborn, Pasquale Minervini, Tim Dettmers, Isabelle Augenstein, Johannes Welbl, Tim Rocktรคschel, Matko Boลกnjak, Jeff Mitchell, Thomas Demeester, Pontus Stenetorp, Sebastian Riedel
arXiv ID
1806.08727
Category
cs.CL: Computation & Language
Cross-listed
cs.LG,
stat.ML
Citations
13
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
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.
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