UW-MRS: Leveraging a Deep Grammar for Robotic Spatial Commands
نویسنده
چکیده
This paper describes a deep-parsing approach to SemEval-2014 Task 6, a novel context-informed supervised parsing and semantic analysis problem in a controlled domain. The system comprises a handbuilt rule-based solution based on a preexisting broad coverage deep grammar of English, backed up by a off-the-shelf datadriven PCFG parser, and achieves the best score reported among the task participants.
منابع مشابه
RoBox: CCG with Structured Perceptron for Supervised Semantic Parsing of Robotic Spatial Commands
We use a Combinatory Categorial Grammar (CCG) parser with a structured perceptron learner to address Shared Task 6 of SemEval-2014, Supervised Semantic Parsing of Robotic Spatial Commands. Our system reaches an accuracy of 79% ignoring spatial context and 87% using the spatial planner, showing that CCG can successfully be applied to the task.
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تاریخ انتشار 2014