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Showing 1 to 7 of 7 for “"semantic parser"”.
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An Explainable Semantic Parser for End-User Development
… programming languages, where a tailored semantic parser can translate a natural language utterance to a formal command representation able to be processed by a computational machine. Currently, semantic parsers are typically built on the top of a learning method that defines its …
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A General Purpose Semantic Parser Using FrameNet and WordNet®.
… correspondence between syntactic rules and semantic rules. But such systems can only be applied to limited fragments of English. In this thesis, we propose a general-purpose shallow semantic parser which utilizes a semantic network (WordNet), and a frame dataset (FrameNet). Semantic …
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Grounded semantic parsing using captioned videos
We develop a semantic parser which is trained in a grounded setting using pairs of videos captioned with sentences. This setting is both data-efficient requiring little annotation and far more similar to the experience of children where they observe their environment and listen to speakers. The …
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Learning meaning in Genesis
… sentences into a variety of more meaningful semantic representations. I reproduced the functionality of these rules by training the existing rule-learning program UNDERSTAND with 43 human-readable examples of English sentences and corresponding semantic representations, resulting in 18 rules. …
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Domain knowledge acquisition via language grounding
… planning in a complex virtual world and input parser generation from input format specifications. In the first application, we propose a reinforcement learning framework to jointly learn to predict precondition relations from text and to perform high-level planning guided by those relations. …
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Tracing the Precursors and Amplifiers of Conflict in the Information Age: An NLP Inquiry of Tensions, Political Communication, and Misinformation
… By showcasing the potential of a frame-semantic parser, I am able to quantify the precursors that contribute to conflict and examine the potential for enhancing prediction models with greater qualitative depth. This chapter utilizes a rich but under-examined data source, news articles, …
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Learning Language with Multimodal Models
… multimodal domains. The first approach trains a semantic parser to map from natural language to logical forms using captioned videos, learning without parse trees or any other annotations. The second approach moves from simply observing videos to a more dynamic setup using a robotic simulator and …