@inproceedings{boratko-etal-2018-interface,
title = "An Interface for Annotating Science Questions",
author = "Boratko, Michael and
Padigela, Harshit and
Mikkilineni, Divyendra and
Yuvraj, Pritish and
Das, Rajarshi and
McCallum, Andrew and
Chang, Maria and
Fokoue, Achille and
Kapanipathi, Pavan and
Mattei, Nicholas and
Musa, Ryan and
Talamadupula, Kartik and
Witbrock, Michael",
editor = "Blanco, Eduardo and
Lu, Wei",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-2018/",
doi = "10.18653/v1/D18-2018",
pages = "102--107",
abstract = "Recent work introduces the AI2 Reasoning Challenge (ARC) and the associated ARC dataset that partitions open domain, complex science questions into an Easy Set and a Challenge Set. That work includes an analysis of 100 questions with respect to the types of knowledge and reasoning required to answer them. However, it does not include clear definitions of these types, nor does it offer information about the quality of the labels or the annotation process used. In this paper, we introduce a novel interface for human annotation of science question-answer pairs with their respective knowledge and reasoning types, in order that the classification of new questions may be improved. We build on the classification schema proposed by prior work on the ARC dataset, and evaluate the effectiveness of our interface with a preliminary study involving 10 participants."
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%0 Conference Proceedings
%T An Interface for Annotating Science Questions
%A Boratko, Michael
%A Padigela, Harshit
%A Mikkilineni, Divyendra
%A Yuvraj, Pritish
%A Das, Rajarshi
%A McCallum, Andrew
%A Chang, Maria
%A Fokoue, Achille
%A Kapanipathi, Pavan
%A Mattei, Nicholas
%A Musa, Ryan
%A Talamadupula, Kartik
%A Witbrock, Michael
%Y Blanco, Eduardo
%Y Lu, Wei
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F boratko-etal-2018-interface
%X Recent work introduces the AI2 Reasoning Challenge (ARC) and the associated ARC dataset that partitions open domain, complex science questions into an Easy Set and a Challenge Set. That work includes an analysis of 100 questions with respect to the types of knowledge and reasoning required to answer them. However, it does not include clear definitions of these types, nor does it offer information about the quality of the labels or the annotation process used. In this paper, we introduce a novel interface for human annotation of science question-answer pairs with their respective knowledge and reasoning types, in order that the classification of new questions may be improved. We build on the classification schema proposed by prior work on the ARC dataset, and evaluate the effectiveness of our interface with a preliminary study involving 10 participants.
%R 10.18653/v1/D18-2018
%U https://aclanthology.org/D18-2018/
%U https://doi.org/10.18653/v1/D18-2018
%P 102-107
Markdown (Informal)
[An Interface for Annotating Science Questions](https://aclanthology.org/D18-2018/) (Boratko et al., EMNLP 2018)
ACL
- Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, and Michael Witbrock. 2018. An Interface for Annotating Science Questions. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 102–107, Brussels, Belgium. Association for Computational Linguistics.