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Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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What About the Precedent: An Information-Theoretic Analysis of Common Law
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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Finding Concept-specific Biases in Form–Meaning Associations
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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A Non-Linear Structural Probe
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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| 6 |
How (Non-)Optimal is the Lexicon?
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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| 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
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| 8 |
Backtranslation feedback improves user confidence in MT, not quality
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| 9 |
From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations
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In: Trans Assoc Comput Linguist (2018)
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UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection
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TAXI at SemEval-2016 Task 13: a taxonomy induction method based on lexico-syntactic patterns, substrings and focused crawling
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| 12 |
Temporal Annotation in the Clinical Domain.
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In: Transactions of the Association for Computational Linguistics, vol 2 (2014)
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| 13 |
Discovering body site and severity modifiers in clinical texts
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| 14 |
An Annotation Framework for Dense Event Ordering
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In: DTIC (2014)
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Abstract:
Today s event ordering research is heavily dependent on annotated corpora. Current corpora influence shared evaluations and drive algorithm development. Partly due to this dependence, most research focuses on partial orderings of a document s events. For instance, the TempEval competitions and the TimeBank only annotate small portions of the event graph, focusing on the most salient events or on specific types of event pairs (e.g., only events in the same sentence). Deeper temporal reasoners struggle with this sparsity because the entire temporal picture is not represented. This paper proposes a new annotation process with a mechanism to force annotators to label connected graphs. It generates 10 times more relations per document than the TimeBank, and our TimeBank-Dense corpus is larger than all current corpora. We hope this process and its dense corpus encourages research on new global models with deeper reasoning. ; Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 501 506, Baltimore, Maryland, USA, June 23-25 2014.
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Keyword:
*DATA BASES; ALGORITHMS; GRAPHS; Information Science; SEMANTICS; TIMEBANK-DENSE
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URL: http://www.dtic.mil/docs/citations/ADA624169
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA624169
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