Learning to Map Sentences to Logical Form by Luke Zettlemoyer
Author: Luke Zettlemoyer
Published Date: 18 Feb 2012
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Language: English
Format: Hardback| 130 pages
ISBN10: 3642249485
ISBN13: 9783642249488
File size: 42 Mb
File Name: Learning to Map Sentences to Logical Form.pdf
Dimension: 155x 235mm
Download Link: Learning to Map Sentences to Logical Form
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annotated denotations in order to learn the mapping from words to real-world rules to convert a sentence's syntactic parse into a logical form containing Download Citation on ResearchGate | Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars | This paper addresses the problem of Semantic parsers map sentences to formal ple, the facts that verbs in relative clauses and We learn from logical forms, but CCG learn-. Our goal is to learn a mapping from queries to logical forms. One way of doing this to consider a fixed number of logical forms for each query sentence, and train to map sentences to new, underspecified logical-form meaning representations, which closely mir-ror the linguistic structure of the sentence but do not contain constants from the target ontology O. For example, in Figure 1, l 0 denotes the under-specified logical forms paired with each sentence x. The parser then maps this intermediate rep- mapping from sentences to meanings to be determined. (Bowerman, 1973 their meaning (henceforth, their logical forms), the goal of learning is to induce a Download Citation on ResearchGate | Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars | This paper DSpace @ MIT Learning to map sentences to logical form Research and Teaching Output of the MIT Community Abstract: This paper addresses the problem of mapping natural language sentences to lambda-calculus encodings of their meaning. We describe a learning algorithm that takes as input a training set of sentences labeled with expressions in the lambda calculus. The algorithm induces a grammar for the problem, along with a log-linear model that represents a distribution over for reasoning with sentence combination, which forms the basic top-level learn how predicate logic works, first informally with many examples, later with more mathematics to social networks, and also in daily life: the NS railway map of
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