WorldTree

A corpus of explanation graphs for elementary science questions supporting multi-hop inference

Peter A. Jansen, Elizabeth Wainwright, Steven Marmorstein, Clayton T Morrison

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

1 Citation (Scopus)

Abstract

Developing methods of automated inference that are able to provide users with compelling human-readable justifications for why the answer to a question is correct is critical for domains such as science and medicine, where user trust and detecting costly errors are limiting factors to adoption. One of the central barriers to training question answering models on explainable inference tasks is the lack of gold explanations to serve as training data. In this paper we present a corpus of explanations for standardized science exams, a recent challenge task for question answering. We manually construct a corpus of detailed explanations for nearly all publicly available standardized elementary science question (approximately 1,680 3 rd through 5 th grade questions) and represent these as “explanation graphs” - sets of lexically overlapping sentences that describe how to arrive at the correct answer to a question through a combination of domain and world knowledge. We also provide an explanation-centered tablestore, a collection of semi-structured tables that contain the knowledge to construct these elementary science explanations. Together, these two knowledge resources map out a substantial portion of the knowledge required for answering and explaining elementary science exams, and provide both structured and free-text training data for the explainable inference task.

Original languageEnglish (US)
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages2732-2740
Number of pages9
ISBN (Electronic)9791095546009
StatePublished - Jan 1 2019
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Publication series

NameLREC 2018 - 11th International Conference on Language Resources and Evaluation

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
CountryJapan
CityMiyazaki
Period5/7/185/12/18

Fingerprint

science
gold
Graph
Inference
medicine
Question Answering
lack
resources
knowledge
World Knowledge
Medicine
Resources
Justification

Keywords

  • Explainable inference
  • Explanations
  • Question answering

ASJC Scopus subject areas

  • Linguistics and Language
  • Education
  • Library and Information Sciences
  • Language and Linguistics

Cite this

Jansen, P. A., Wainwright, E., Marmorstein, S., & Morrison, C. T. (2019). WorldTree: A corpus of explanation graphs for elementary science questions supporting multi-hop inference. In H. Isahara, B. Maegaard, S. Piperidis, C. Cieri, T. Declerck, K. Hasida, H. Mazo, K. Choukri, S. Goggi, J. Mariani, A. Moreno, N. Calzolari, J. Odijk, ... T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 2732-2740). (LREC 2018 - 11th International Conference on Language Resources and Evaluation). European Language Resources Association (ELRA).

WorldTree : A corpus of explanation graphs for elementary science questions supporting multi-hop inference. / Jansen, Peter A.; Wainwright, Elizabeth; Marmorstein, Steven; Morrison, Clayton T.

LREC 2018 - 11th International Conference on Language Resources and Evaluation. ed. / Hitoshi Isahara; Bente Maegaard; Stelios Piperidis; Christopher Cieri; Thierry Declerck; Koiti Hasida; Helene Mazo; Khalid Choukri; Sara Goggi; Joseph Mariani; Asuncion Moreno; Nicoletta Calzolari; Jan Odijk; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. p. 2732-2740 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

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

Jansen, PA, Wainwright, E, Marmorstein, S & Morrison, CT 2019, WorldTree: A corpus of explanation graphs for elementary science questions supporting multi-hop inference. in H Isahara, B Maegaard, S Piperidis, C Cieri, T Declerck, K Hasida, H Mazo, K Choukri, S Goggi, J Mariani, A Moreno, N Calzolari, J Odijk & T Tokunaga (eds), LREC 2018 - 11th International Conference on Language Resources and Evaluation. LREC 2018 - 11th International Conference on Language Resources and Evaluation, European Language Resources Association (ELRA), pp. 2732-2740, 11th International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan, 5/7/18.
Jansen PA, Wainwright E, Marmorstein S, Morrison CT. WorldTree: A corpus of explanation graphs for elementary science questions supporting multi-hop inference. In Isahara H, Maegaard B, Piperidis S, Cieri C, Declerck T, Hasida K, Mazo H, Choukri K, Goggi S, Mariani J, Moreno A, Calzolari N, Odijk J, Tokunaga T, editors, LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA). 2019. p. 2732-2740. (LREC 2018 - 11th International Conference on Language Resources and Evaluation).
Jansen, Peter A. ; Wainwright, Elizabeth ; Marmorstein, Steven ; Morrison, Clayton T. / WorldTree : A corpus of explanation graphs for elementary science questions supporting multi-hop inference. LREC 2018 - 11th International Conference on Language Resources and Evaluation. editor / Hitoshi Isahara ; Bente Maegaard ; Stelios Piperidis ; Christopher Cieri ; Thierry Declerck ; Koiti Hasida ; Helene Mazo ; Khalid Choukri ; Sara Goggi ; Joseph Mariani ; Asuncion Moreno ; Nicoletta Calzolari ; Jan Odijk ; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. pp. 2732-2740 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).
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