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Structured Sentiment Analysis as Dependency Graph Parsing ...
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Transfer and Multi-Task Learning for Noun-Noun Compound Interpretation ...
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SDP 2014 & 2015: Broad Coverage Semantic Dependency Parsing ...
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Abstract:
Introduction SDP 2014 & 2015: Broad Coverage Semantic Dependency Parsing consists of data, tools, system results, and publications associated with the 2014 and 2015 tasks on Broad-Coverage Semantic Dependency Parsing (SDP) conducted in conjunction with the International Workshop on Semantic Evaluation (SemEval) and was developed by the SDP task organizers. SemEval is an ongoing series of evaluations of computational semantic analysis systems intended to explore the nature of meaning in language. It evolved from the Senseval word sense disambiguation series to include semantic analysis tasks outside of word sense disambiguation. Data SDP 2014 & 2015: Broad Coverage Semantic Dependency Parsing is based on English, Chinese and Czech data from the following resources: Treebank-2
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URL: https://dx.doi.org/10.35111/m8h4-6932 https://catalog.ldc.upenn.edu/LDC2016T10
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Combining statistical machine translation and translation memories with domain adaptation
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In: Läubli, Samuel; Fishel, Mark; Volk, Martin; Weibel, Manuela (2013). Combining statistical machine translation and translation memories with domain adaptation. In: NODALIDA 2013, Nordic Conference of Computational Linguistics, Oslo, Norway, 22 May 2013 - 24 May 2013, 331-341. (2013)
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Bootstrapping an Unsupervised Approach for Classifying Agreement and Disagreement
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