Discontinuous Combinatory Constituency Parsing Zhousi Chen and Mamoru Komachi Faculty of Systems Design Tokyo Metropolitan University 6-6 Asahigaoka, Hino, Tokio 191-0065, Japón {chen-zhousi@ed., komachi@}tmu.ac.jp Abstract We extend a pair of continuous combinator- based constituency parsers…
Browsing Categorytacl
Resolución de correferencia a través de un sistema basado en transición seq2seq
Coreference Resolution through a seq2seq Transition-Based System Bernd Bohnet1, Chris Alberti2, Michael Collins2 1Google Research, The Netherlands 2Google Research, EE.UU {bohnetbd,chrisalberti,mjcollins}@google.com Abstract Most recent coreference resolution systems use search algorithms over possible spans to identify…
sentimientoazul: Un corpus para la comprensión
sentimientoazul: A Corpus for Understanding the Emotional Connotation of Color in Context Amith Ananthram1 and Olivia Winn1 and Smaranda Muresan1,2 1Department of Computer Science, Columbia University, USA 2Data Science Institute, Columbia University, EE.UU {amith,olivia,smara}@cs.columbia.edu Abstract…
Domain-Specific Word Embeddings with Structure Prediction
Domain-Specific Word Embeddings with Structure Prediction David Lassner1,2∗ Stephanie Brandl1,2,3∗ Anne Baillot4 Shinichi Nakajima1,2,5 1TU Berlin, Germany 2BIFOLD, Germany 3University of Copenhagen, Denmark 4Le Mans Universit´e, France 5RIKEN Center for AIP, Japón {lassner@tu-berlin.de,brandl@di.ku.dk} ∗Authors contributed…
Mejora del análisis multilingüe de bajos recursos
Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization Thomas Effland Columbia University, USA teffland@cs.columbia.edu Michael Collins Google Research, USA mjcollins@google.com Abstract We present Expected Statistic Regulariza tion (ESR), a novel regularization technique that utilizes low-order…
Locally Typical Sampling
Locally Typical Sampling Clara Meister1 Tiago Pimentel2 Gian Wiher1 Ryan Cotterell1,2 1ETH Z¨urich, Switzerland 2University of Cambridge, UK clara.meister@inf.ethz.ch tp472@cam.ac.uk gian.wiher@inf.ethz.ch ryan.cotterell@inf.ethz.ch Abstract Today’s probabilistic language generators fall short when it comes to producing coherent…
Helpful Neighbors:
Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation Llion Jones† Richard Sproat† Haruko Ishikawa† Alexander Gutkin‡ †Google Japan ‡Google UK {llion,rws,ishikawa,agutkin}@google.com Abstract If one sees the place name Houston Mer- cer Dog Run in New…
OPAL: Ontology-Aware Pretrained Language Model for End-to-End
OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue Zhi Chen1, Yuncong Liu1, Lu Chen1∗, Su Zhu2, Mengyue Wu1, Kai Yu1∗ 1X-LANCE Lab, Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence,…
Meta-Learning a Cross-lingual Manifold for Semantic Parsing
Meta-Learning a Cross-lingual Manifold for Semantic Parsing Tom Sherborne and Mirella Lapata Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB, UK tom.sherborne@ed.ac.uk, mlap@inf.ed.ac.uk Abstract Localizing…
Sobre el papel del precedente negativo en la predicción de resultados jurídicos
On the Role of Negative Precedent in Legal Outcome Prediction Josef Valvoda Ryan Cotterell Simone Teufel University of Cambridge, UK ETH Z¨urich, Suiza {jv406,sht25}@cam.ac.uk ryan.cotterell@inf.ethz.ch Abstract Every legal case sets a precedent by develop- En g…