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An Analysis of Gender Bias in K-12 Assigned Literature Through Comparison of Non-Contextual Word Embedding Models
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Assembling Syntax: Modeling Constituent Questions in a Grammar Engineering Framework
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Collecting and using race and ethnicity information in linguistic studies
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Tracing and Reducing Lexical Ambiguity in Automatically Inferred Grammars
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A Finite-State Morphological Analyzer for Central Alaskan Yup'ik
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Inferring Grammars from Interlinear Glossed Text: Extracting Typological and Lexical Properties for the Automatic Generation of HPSG Grammars
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Linguistic fundamentals for natural language processing II: 100 essentials from semantics and pragmatics
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Braiding Language (by Computer): Lushootseed Grammar Engineering
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Modeling Clausal Complementation for a Grammar Engineering Resource
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In: Proceedings of the Society for Computation in Linguistics (2019)
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Incorporating deep visual features into multiobjective based multi-view search results clustering
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In: Mitra, Sayantan, Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 , Saha, Sriparna and Way, Andy orcid:0000-0001-5736-5930 (2018) Incorporating deep visual features into multiobjective based multi-view search results clustering. In: 27th International Conference on Computational Linguistics, 20-26 Aug 2018, Santa Fe, NM, USA. (2018)
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Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs
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Abstract:
Large scale knowledge graphs (KGs) such as Freebase are generally incomplete. Reasoning over multi-hop (mh) KG paths is thus an important capability that is needed for question answering or other NLP tasks that require knowledge about the world. mh-KG reasoning includes diverse scenarios, e.g., given a head entity and a relation path, predict the tail entity; or given two enti- ties connected by some relation paths, predict the unknown relation between them. We present ROPs, recurrent one-hop predictors, that predict entities at each step of mh-KB paths by using recurrent neural networks and vector representations of entities and relations, with two benefits: (i) modeling mh-paths of arbitrary lengths while updating the entity and relation representations by the training signal at each step; (ii) handling different types of mh-KG reasoning in a unified framework. Our models show state-of-the-art for two important multi-hop KG reasoning tasks: Knowledge Base Completion and Path Query Answering
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Keyword:
ddc:000; ddc:004; ddc:400; ddc:410
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URL: https://epub.ub.uni-muenchen.de/61860/1/C18-1200.pdf https://doi.org/10.5282/ubm/epub.61860 http://nbn-resolving.de/urn:nbn:de:bvb:19-epub-61860-0 https://epub.ub.uni-muenchen.de/61860/
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A Parametric Implementation of Valence-changing Morphology in the LinGO Grammar Matrix
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