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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; ., Giovanna Maria Dora; Bhattacharya, Rohit. - : Underline Science Inc., 2022 BASE Show details 2 Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Mamidi, Radhika; Pant, Kartikey. - : Underline Science Inc., 2022 BASE Show details 3 Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hou, Yifan; Sachan, Mrinmaya. - : Underline Science Inc., 2022 BASE Show details 4 Formalization of AMR Inference via Hybrid Logic Tableaux ... Goldner, Eli Tecumseh. - : Brandeis University, 2022 Abstract: AMR and its extensions have become popular in semantic representation due to their ease of annotation by non-experts, attention to the predicative core of sentences, and abstraction away from syntactic matter. An area where AMR and its extensions warrant improvement is formalization and suitability for inference, where it is lacking compared to other semantic representations, such as description logics, episodic logic, and discourse representation theory. This thesis presents a formalization of inference over a merging of Donatelli et al.’s (2018) AMR extension for tense and aspect with Pustejovsky et al.’s (2019) AMR extension for quantification and scope. Inference is modeled with a merging of Hansen’s (2007) tableau method for first-order hybrid logic with varying domain semantics (FHL) and Blackburn and Jørgensen’s (2012) tableau method for basic hybrid tense logic (BHTL). We motivate the merging of these AMR variants, present their interpretation and inference in the combination of FHL and BHTL, which ... Keyword: Abstract Meaning Representation; AMR; automated reasoning; Computational Linguistics; hybrid logic; Knowledge Representation; semantic representation; Semantics; tableau URL: https://dx.doi.org/10.48617/etd.45 https://scholarworks.brandeis.edu/esploro/outputs/graduate/9924022111401921 BASE Hide details

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