Eidos, INDRA, & Delphi: From free text to executable causal models

Rebecca Sharp, Adarsh Pyarelal, Benjamin M. Gyori, Keith Alcock, Egoitz Laparra, Marco A. Valenzuela-Escarcega, Ajay Nagesh, Vikas Yadav, John A. Bachman, Zheng Tang, Heather Lent, Fan Luo, Mithun Paul, Steven Bethard, Kobus Barnard, Clayton T. Morrison, Mihai Surdeanu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Building causal models of complicated phenomena such as food insecurity is currently a slow and labor-intensive manual process. In this paper, we introduce an approach that builds executable probabilistic models from raw, free text. The proposed approach is implemented through three systems: Eidos1, INDRA2 and Delphi3. Eidos is an open-domain machine reading system designed to extract causal relations from natural language. It is rule-based, allowing for rapid domain transfer, customizability, and interpretability. INDRA aggregates multiple sources of causal information and performs assembly to create a coherent knowledge base and assess its reliability. This assembled knowledge serves as the starting point for modeling. Delphi is a modeling framework that assembles quantified causal fragments and their contexts into executable probabilistic models that respect the semantics of the original text and can be used to support decision making.

Original languageEnglish (US)
Title of host publicationNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies - Proceedings of the Demonstrations Session
PublisherAssociation for Computational Linguistics (ACL)
Pages42-47
Number of pages6
ISBN (Electronic)9781950737161
StatePublished - 2019
Event2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States
Duration: Jun 2 2019Jun 7 2019

Publication series

NameNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Demonstrations Session

Conference

Conference2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
CountryUnited States
CityMinneapolis
Period6/2/196/7/19

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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    Sharp, R., Pyarelal, A., Gyori, B. M., Alcock, K., Laparra, E., Valenzuela-Escarcega, M. A., Nagesh, A., Yadav, V., Bachman, J. A., Tang, Z., Lent, H., Luo, F., Paul, M., Bethard, S., Barnard, K., Morrison, C. T., & Surdeanu, M. (2019). Eidos, INDRA, & Delphi: From free text to executable causal models. In NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Demonstrations Session (pp. 42-47). (NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Demonstrations Session). Association for Computational Linguistics (ACL).