SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM) Marine Carpuat Nathan Schneider Dirk Hovy Anders Johannsen School of Informatics

Source URL: www.cs.cmu.edu

NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity John P. McCrae and Kartik Asooja and Nitish Aggarwal and Paul Buitelaar Insight Centre for Data Analytics National Univer

Source URL: aclweb.org

Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora Abstract A word’s sentiment depends on the domain in which it is used. Computational social science research thus requires sentiment lexicons that

Source URL: arxiv.org

• Computational linguistics
• Natural language processing
• Linguistics
• Artificial intelligence
• Language
• Semantics
• Artificial neural networks
• Speech recognition
• Sentiment analysis
• SemEval
• Semantic lexicon
• Lexical

9. KONFERENCA JEZIKOVNE TEHNOLOGIJE Informacijska družba - IS 2014 9th Language Technologies Conference Information Society - IS 2014

Source URL: nl.ijs.si

• Computational linguistics
• Computing
• Linguistics
• Applied linguistics
• Named-entity recognition
• TimeML
• SemEval
• Temporal expressions
• Part-of-speech tagging
• Natural language processing
• Question answering
• Trigram tagger

Most babies are little and most problems are huge: Compositional Entailment in Adjective-Nouns Ellie Pavlick University of Pennsylvania

Source URL: www.cis.upenn.edu

• Logic
• Logical consequence
• Philosophy of logic
• Textual entailment
• SemEval
• Entailment
• Monotonicity of entailment
• Implication
• Implicature
• Argument
• WordNet
• Machine learning

PLIS: a Probabilistic Lexical Inference System Eyal Shnarch1 , Erel Segal-haLevi1 , Jacob Goldberger2 , Ido Dagan1 1 Computer Science Department, Bar-Ilan University, Israel 2 Faculty of Engineering, Bar-Ilan University,

Source URL: u.cs.biu.ac.il

• Logic
• Linguistics
• Computational linguistics
• Natural language processing
• Semantics
• Lexical semantics
• Philosophy
• Reasoning
• Inference
• Word-sense disambiguation
• WordNet
• SemEval

Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase Peter D. Turney National Research Council Canada Information and Communications Technologies Ottawa, Ontario, Canada, K1A 0R6

Source URL: www.aclweb.org

• Computational linguistics
• Algebra
• Linguistics
• Natural language processing
• Applied linguistics
• Semantics
• Vectors
• Linear algebra
• N-gram
• Semantic similarity
• SemEval
• Bigram

HiEve: A Corpus for Extracting Event Hierarchies from News Stories 1 ˇ Goran Glavaˇs1 , Jan Snajder , Parisa Kordjamshidi2 , and Marie-Francine Moens2 1

Source URL: www.lrec-conf.org

• Computing
• Computational linguistics
• Academia
• Metaphysics
• Natural language processing
• Semantics
• TimeML
• SemEval
• Event
• Spatialtemporal reasoning
• Process philosophy
• Temporal annotation

SENSEVAL-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, Barcelona, Spain, July 2004 Association for Computational Linguistics The University of Maryland SENSEVAL-3 System

Source URL: drona.csa.iisc.ernet.in

• Linguistics
• Computational linguistics
• Semantics
• Language
• Natural language processing
• Word-sense disambiguation
• Lexical semantics
• SemEval
• WordNet
• Word sense
• Machine translation
• Part-of-speech tagging

The ACL RD-TEC Annotation Guideline A Reference Dataset for the Evaluation of Automatic Term Recognition and Classification Version 2.6 Anne-Kathrin Schumann and Behrang QasemiZadeh , me@a

Source URL: pars.ie

• Linguistics
• Computational linguistics
• Language
• Natural language processing
• Applied linguistics
• Semantics
• Reference
• SemEval
• Annotation
• Word-sense disambiguation
• Rule-based machine translation
• Machine translation