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- W3019501371 abstract "In the last decade, there has been a surge of work contributing to commonsense reasoning and language understanding. Several datasets and knowledge representations for question answering, coreference resolution, and inference tasks have been discussed and built upon in the NLP community. However, these focus on declarative knowledge, or factual knowledge describing an entity or event. In contrast, a large body of research that has not been discussed, is reasoning and language understanding with procedural/how-to knowledge, or the knowledge used in completing a task or process (e.g., navigation instructions, recipes, repair guides, etc.). Several procedural knowledge bases, benchmark datasets, and information extraction methods, have enabled the various natural language understanding tasks with procedural knowledge (also known as procedural knowledge understanding). This paper seeks to provide an overview of the work in procedural knowledge understanding, and information extraction, acquisition, and representation with procedures, to promote discussion and provide a better understanding of procedural knowledge applications and future challenges." @default.
- W3019501371 created "2020-05-01" @default.
- W3019501371 creator A5031540690 @default.
- W3019501371 creator A5060766682 @default.
- W3019501371 date "2019-12-01" @default.
- W3019501371 modified "2023-09-25" @default.
- W3019501371 title "Recent Trends in Natural Language Understanding for Procedural Knowledge" @default.
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- W3019501371 doi "https://doi.org/10.1109/csci49370.2019.00082" @default.
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