Corpus ID: 17380649

TabMCQ: A Dataset of General Knowledge Tables and Multiple-choice Questions

@article{Jauhar2016TabMCQAD,
  title={TabMCQ: A Dataset of General Knowledge Tables and Multiple-choice Questions},
  author={Sujay Kumar Jauhar and Peter D. Turney and E. Hovy},
  journal={ArXiv},
  year={2016},
  volume={abs/1602.03960}
}
We describe two new related resources that facilitate modelling of general knowledge reasoning in 4th grade science exams. The first is a collection of curated facts in the form of tables, and the second is a large set of crowd-sourced multiple-choice questions covering the facts in the tables. Through the setup of the crowd-sourced annotation task we obtain implicit alignment information between questions and tables. We envisage that the resources will be useful not only to researchers working… Expand
5 Citations
Question Answering on Scholarly Knowledge Graphs
  • Highly Influenced
  • PDF
Automatic question generation and answer assessment: a survey
  • PDF
A Relation-Centric View of Semantic Representation Learning
  • 2
  • PDF
Creating A Neural Pedagogical Agent by Jointly Learning to Review and Assess
  • 8
  • PDF

References

SHOWING 1-10 OF 14 REFERENCES
Compositional Semantic Parsing on Semi-Structured Tables
  • 284
  • PDF
Exploring Markov Logic Networks for Question Answering
  • 33
  • PDF
Open question answering over curated and extracted knowledge bases
  • 336
  • PDF
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
  • 800
  • Highly Influential
  • PDF
Learning surface text patterns for a Question Answering System
  • 900
  • PDF
Neural Enquirer: Learning to Query Tables
  • 42
  • PDF
Answering Table Queries on the Web using Column Keywords
  • 107
  • PDF
Quantitative evaluation of passage retrieval algorithms for question answering
  • 329
  • PDF
Neural enquirer: learning to query tables in natural language
  • 68
  • PDF
WebTables: exploring the power of tables on the web
  • 605
  • PDF
...
1
2
...