Crowdsourcing Question-Answer Meaning Representations

@inproceedings{Michael2018CrowdsourcingQM,
  title={Crowdsourcing Question-Answer Meaning Representations},
  author={Julian Michael and Gabriel Stanovsky and Luheng He and Ido Dagan and Luke S. Zettlemoyer},
  booktitle={NAACL-HLT},
  year={2018}
}
We introduce Question-Answer Meaning Representations (QAMRs), which represent the predicate-argument structure of a sentence as a set of question-answer pairs. We develop a crowdsourcing scheme to show that QAMRs can be labeled with very little training, and gather a dataset with over 5,000 sentences and 100,000 questions. A qualitative analysis… CONTINUE READING