Modeling Biological Processes for Reading Comprehension

@inproceedings{Berant2014ModelingBP,
  title={Modeling Biological Processes for Reading Comprehension},
  author={Jonathan Berant and V. Srikumar and P. Chen and A. V. Linden and Brittany Harding and Brad Huang and Peter Clark and Christopher D. Manning},
  booktitle={EMNLP},
  year={2014}
}
  • Jonathan Berant, V. Srikumar, +5 authors Christopher D. Manning
  • Published in EMNLP 2014
  • Computer Science
  • Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. [...] Key Method To answer the questions, we first predict a rich structure representing the process in the paragraph. Then, we map the question to a formal query, which is executed against the predicted structure. We demonstrate that answering questions via predicted structures substantially improves accuracy over baselines that use shallower representations.Expand Abstract

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 42 REFERENCES
    WordNet : an electronic lexical database
    • 12,339
    • Open Access
    The Stanford CoreNLP Natural Language Processing Toolkit
    • 4,680
    • Open Access
    The Proposition Bank: An Annotated Corpus of Semantic Roles
    • 2,191
    • Highly Influential
    • Open Access
    Semantic Parsing on Freebase from Question-Answer Pairs
    • 947
    • Open Access
    Toward an Architecture for Never-Ending Language Learning
    • 1,466
    • Open Access
    Identifying Relations for Open Information Extraction
    • 1,094
    • Open Access
    Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars
    • 736
    • Open Access
    English Verb Classes and Alternations: A Preliminary Investigation
    • 2,915
    • Open Access
    Deep Read: A Reading Comprehension System
    • 207
    • Open Access
    MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text
    • 449
    • Open Access