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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 – 15 of 15 1 Do pretrained transformers infer telicity like humans? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Lucy; Bethard, Steven. - : Underline Science Inc., 2021 BASE Show details 2 Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing Hall Maudslay, Rowan; Cotterell, Ryan In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 3 What About the Precedent: An Information-Theoretic Analysis of Common Law Teufel, Simone; Valvoda, Josef; Stoehr, Niklas... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 4 Finding Concept-specific Biases in Form–Meaning Associations Roark, Brian; Blasi, Damián; Pimentel, Tiago... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 5 A Non-Linear Structural Probe Pimentel, Tiago; Cotterell, Ryan; Saphra, Naomi... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 6 How (Non-)Optimal is the Lexicon? Cotterell, Ryan; Pimentel, Tiago; Nikkarinen, Irene... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 7 Consumer Cynicism Identification for Spanish Reviews using a Spanish Transformer Model ; Identificación del cinismo del consumidor para reseñas en español utilizando un modelo de transformador español González-López, Samuel; Bethard, Steven; Encinas Orozco, Francisca Cecilia. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2021 BASE Show details 8 Backtranslation feedback improves user confidence in MT, not quality Obregón, Mateo; Fomicheva, Marina; Novák, Michal. - : Association for Computational Linguistics, 2021 BASE Show details 9 From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations Laparra, Egoitz; Xu, Dongfang; Bethard, Steven In: Trans Assoc Comput Linguist (2018) BASE Show details 10 UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection Sadeque, Farig; Xu, Dongfang; Bethard, Steven. - 2017 BASE Show details 11 TAXI at SemEval-2016 Task 13: a taxonomy induction method based on lexico-syntactic patterns, substrings and focused crawling Fairon, Cédrick; Faralli, Stefano; Panchenko, Alexander. - : Association for Computational Linguistics, 2016 BASE Show details 12 Temporal Annotation in the Clinical Domain. Styler, William F; Bethard, Steven; Finan, Sean... In: Transactions of the Association for Computational Linguistics, vol 2 (2014) BASE Show details 13 Discovering body site and severity modifiers in clinical texts Dligach, Dmitriy; Bethard, Steven; Becker, Lee. - : BMJ Publishing Group, 2014 BASE Show details 14 An Annotation Framework for Dense Event Ordering Cassidy, Taylor; McDowell, Bill; Chambers, Nathanel... In: DTIC (2014) BASE Show details 15 Temporal Annotation in the Clinical Domain Styler, William F.; Bethard, Steven; Finan, Sean; Palmer, Martha; Pradhan, Sameer; de Groen, Piet C; Erickson, Brad; Miller, Timothy; Lin, Chen; Savova, Guergana; Pustejovsky, James. - 2014 Abstract: This article discusses the requirements of a formal specification for the annotation of temporal information in clinical narratives. We discuss the implementation and extension of ISO-TimeML for annotating a corpus of clinical notes, known as the THYME corpus. To reflect the information task and the heavily inference-based reasoning demands in the domain, a new annotation guideline has been developed, “the THYME Guidelines to ISO-TimeML (THYME-TimeML)”. To clarify what relations merit annotation, we distinguish between linguistically-derived and inferentially-derived temporal orderings in the text. We also apply a top performing TempEval 2013 system against this new resource to measure the difficulty of adapting systems to the clinical domain. The corpus is available to the community and has been proposed for use in a SemEval 2015 task. Keyword: Article URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5657277/ BASE Hide details

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