Equation Parsing: Mapping Sentences to Grounded Equations
September 28, 2016 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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Authors
Subhro Roy, Shyam Upadhyay, Dan Roth
arXiv ID
1609.08824
Category
cs.CL: Computation & Language
Citations
47
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
4 months ago
Abstract
Identifying mathematical relations expressed in text is essential to understanding a broad range of natural language text from election reports, to financial news, to sport commentaries to mathematical word problems. This paper focuses on identifying and understanding mathematical relations described within a single sentence. We introduce the problem of Equation Parsing -- given a sentence, identify noun phrases which represent variables, and generate the mathematical equation expressing the relation described in the sentence. We introduce the notion of projective equation parsing and provide an efficient algorithm to parse text to projective equations. Our system makes use of a high precision lexicon of mathematical expressions and a pipeline of structured predictors, and generates correct equations in $70\%$ of the cases. In $60\%$ of the time, it also identifies the correct noun phrase $\rightarrow$ variables mapping, significantly outperforming baselines. We also release a new annotated dataset for task evaluation.
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