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Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering
Clayton Greenberg
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Asad Sayeed
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Vera Demberg
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Paper Details:
Month: May–June
Year: 2015
Location: Denver, Colorado
Venue:
NAACL |
Citations
URL
Event participant modelling with neural networks
Ottokar Tilk
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Vera Demberg
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Asad Sayeed
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Dietrich Klakow
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Stefan Thater
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Representing Verbs with Rich Contexts: an Evaluation on Verb Similarity
Emmanuele Chersoni
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Enrico Santus
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Alessandro Lenci
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Philippe Blache
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Chu-Ren Huang
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Measuring Thematic Fit with Distributional Feature Overlap
Enrico Santus
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Emmanuele Chersoni
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Alessandro Lenci
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Philippe Blache
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Rollenwechsel-English: a large-scale semantic role corpus
Asad Sayeed
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Pavel Shkadzko
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Vera Demberg
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A vision-grounded dataset for predicting typical locations for verbs
Nelson Mukuze
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Anna Rohrbach
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Vera Demberg
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Bernt Schiele
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Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders
Simon Šuster
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Ivan Titov
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Gertjan van Noord
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Vector-space calculation of semantic surprisal for predicting word pronunciation duration
Asad Sayeed
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Stefan Fischer
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Vera Demberg
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Learning distributed event representations with a multi-task approach
Xudong Hong
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Asad Sayeed
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Vera Demberg
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Thematic fit evaluation: an aspect of selectional preferences
Asad Sayeed
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Clayton Greenberg
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Vera Demberg
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Is Structure Necessary for Modeling Argument Expectations in Distributional Semantics?
Emmanuele Chersoni
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Enrico Santus
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Philippe Blache
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Alessandro Lenci
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Modeling Violations of Selectional Restrictions with Distributional Semantics
Emmanuele Chersoni
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Adrià Torrens Urrutia
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Philippe Blache
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Alessandro Lenci
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http://rollen.mmci.uni-saarland.de/
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