Towards Addressing the Winograd Schema Challenge - Building and Using a Semantic Parser and a Knowledge Hunting Module
Abstract
Concerned about the Turing test's ability to correctly evaluate if a system exhibits human-like intelligence, the Winograd Schema Challenge (WSC) has been proposed as an alternative. A Winograd Schema consists of a sentence and a question. The answers to the questions are intuitive for humans but are designed to be difficult for machines, as they require various forms of commonsense knowledge about the sentence. In this paper we demonstrate our progress towards addressing the WSC. We present an approach that identifies the knowledge needed to answer a challenge question, hunts down that knowledge from text repositories, and then reasons with them to come up with the answer. In the process we develop a semantic parser (www.kparser.org). We show that our approach works well with respect to a subset of Winograd schemas.
Cite
Text
Sharma et al. "Towards Addressing the Winograd Schema Challenge - Building and Using a Semantic Parser and a Knowledge Hunting Module." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Sharma et al. "Towards Addressing the Winograd Schema Challenge - Building and Using a Semantic Parser and a Knowledge Hunting Module." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/sharma2015ijcai-addressing/)BibTeX
@inproceedings{sharma2015ijcai-addressing,
title = {{Towards Addressing the Winograd Schema Challenge - Building and Using a Semantic Parser and a Knowledge Hunting Module}},
author = {Sharma, Arpit and Vo, Nguyen Ha and Aditya, Somak and Baral, Chitta},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {1319-1325},
url = {https://mlanthology.org/ijcai/2015/sharma2015ijcai-addressing/}
}