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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 – 8 of 8 1 Spanish Abstract Meaning Representation: Annotation of a General Corpus ... Wein, Shira; Donatelli, Lucia; Ricker, Ethan. - : arXiv, 2022 BASE Show details 2 Compositional Generalization Requires Compositional Parsers ... Weißenhorn, Pia; Yao, Yuekun; Donatelli, Lucia. - : arXiv, 2022 BASE Show details 3 Aligning Actions Across Recipe Graphs ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Biswas, Debanjali; Donatelli, Lucia. - : Underline Science Inc., 2021 BASE Show details 4 Normalizing Compositional Structures Across Graphbanks ... Donatelli, Lucia; Groschwitz, Jonas; Koller, Alexander. - : arXiv, 2020 BASE Show details 5 A Continuation Semantics for Abstract Meaning Representation ... The 28th International Conference on Computational Linguistics 2020; Donatelli, Lucia; Lai, Kenneth. - : Underline Science Inc., 2020 BASE Show details 6 Graph-to-Graph Meaning Representation Transformations for Human-Robot Dialogue Abrams, Mitchell; Bonial, Claire; Donatelli, Lucia In: Proceedings of the Society for Computation in Linguistics (2020) Abstract: In support of two-way human-robot communication, we leverage Abstract Meaning Representation (AMR) to capture the core semantic content of natural language search and navigation instructions. In order to effectively map AMR to a constrained robot action specification, we develop a set of in-domain, task-specific AMR graphs augmented with speech act and tense and aspect information not found in the original AMR. This paper presents our efforts and results in transforming AMR graphs into our in-domain graphs by employing both rule-based and classifier-based methods, thereby bridging the gap from entirely unconstrained natural language input to a fixed set of robot actions. Keyword: aspect; Computational Linguistics; Human-robot dialogue; meaning representation; robot; speech acts; tense URL: https://scholarworks.umass.edu/scil/vol3/iss1/50 https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1133&context=scil BASE Hide details 7 Abstract Meaning Representation for Human-Robot Dialogue Bonial, Claire N; Donatelli, Lucia; Ervin, Jessica... In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 8 Tense and Aspect Semantics for Sentential AMR Donatelli, Lucia; Schneider, Nathan; Croft, William... In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details

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