Title: Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches
Abstract: Commonsense knowledge and commonsense reasoning are some of the main
bottlenecks in machine intelligence. In the NLP community, many benchmark
datasets and tasks have been created to address commonsense reasoning for
language understanding. These tasks are designed to assess machines' ability to
acquire and learn commonsense knowledge in order to reason and understand
natural language text. As these tasks become instrumental and a driving force
for commonsense research, this paper aims to provide an overview of existing
tasks and benchmarks, knowledge resources, and learning and inference
approaches toward commonsense reasoning for natural language understanding.
Through this, our goal is to support a better understanding of the state of the
art, its limitations, and future challenges.
Publication Year: 2019
Publication Date: 2019-04-02
Language: en
Type: article
Access and Citation
Cited By Count: 51
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