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1
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering ...
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2
Multilingual ATIS
Upadhyay, Shyam; Hakkani-Tur, Dilek; Tur, Gokhan. - : Linguistic Data Consortium, 2019. : https://www.ldc.upenn.edu, 2019
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3
Multilingual ATIS ...
Upadhyay, Shyam; Hakkani-Tur, Dilek; Tur, Gokhan. - : Linguistic Data Consortium, 2019
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4
Exploiting Cross-Lingual Representations For Natural Language Processing
In: Publicly Accessible Penn Dissertations (2019)
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5
Exploiting Cross-lingual Representations for Natural Language Processing
In: Dissertations available from ProQuest (2019)
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6
Joint Multilingual Supervision for Cross-lingual Entity Linking ...
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7
Bootstrapping Transliteration with Constrained Discovery for Low-Resource Languages ...
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8
Robust Cross-lingual Hypernymy Detection using Dependency Context ...
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9
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context ...
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10
Equation Parsing: Mapping Sentences to Grounded Equations ...
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 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1609.08824
https://dx.doi.org/10.48550/arxiv.1609.08824
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11
Cross-lingual Models of Word Embeddings: An Empirical Comparison ...
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