Abstract is missing.
- Finite state intensional semanticsMats Rooth. [doi]
- If Sentences Could See: Investigating Visual Information for Semantic Textual SimilarityGoran Glavas, Ivan Vulic, Simone Paolo Ponzetto. [doi]
- Towards an Inferential Lexicon of Event Selecting Predicates for FrenchIngrid Falk, Fabienne Martin. [doi]
- A Type-Theoretical system for the FraCaS test suite: Grammatical Framework meets CoqJean-Philippe Bernardy, Stergios Chatzikyriakidis. [doi]
- Learning to Compose Spatial Relations with Grounded Neural Language ModelsMehdi Ghanimifard, Simon Dobnik. [doi]
- Is Structure Necessary for Modeling Argument Expectations in Distributional Semantics?Emmanuele Chersoni, Enrico Santus, Philippe Blache, Alessandro Lenci. [doi]
- Extracting hypernym relations from Wikipedia disambiguation pages : comparing symbolic and machine learning approachesMouna Kamel, Cássia Trojahn dos Santos, Adel Ghamnia, Nathalie Aussenac-Gilles, Cécile Fabre. [doi]
- A Geometric Method for Detecting Semantic CoercionStephen McGregor, Elisabetta Jezek, Matthew Purver, Geraint A. Wiggins. [doi]
- Defeasible AceRules: A PrototypeMartin Diller, Adam Z. Wyner, Hannes Strass. [doi]
- Extracting word lists for domain-specific implicit opinions from corporaNúria Bertomeu Castelló, Manfred Stede. [doi]
- A constrained graph algebra for semantic parsing with AMRsJonas Groschwitz, Meaghan Fowlie, Mark Johnson, Alexander Koller. [doi]
- Semantic Composition via Probabilistic Model TheoryGuy Emerson, Ann A. Copestake. [doi]
- Semantic Variation in Online Communities of PracticeMarco Del Tredici, Raquel Fernández. [doi]
- When Conditional Logic met Connexive LogicMathieu Vidal. [doi]
- Comprehensive annotation of cross-linguistic variation in tense and aspect categoriesMark-Matthias Zymla. [doi]
- Exploring Substitutability through Discourse Adverbials and Multiple JudgmentsHannah Rohde, Anna Dickinson, Nathan Schneider, Annie Louis, Bonnie L. Webber. [doi]
- Coarse Semantic Classification of Rare Nouns Using Cross-Lingual Data and Recurrent Neural NetworksOliver Hellwig. [doi]