August 3-4 2017, Vancouver, Canada
Co-located with ACL 2017

We are pleased to announce that SIGLEX and SIGSEM, special interest groups of the ACL, are organizing the 6th Joint Conference on Lexical and Computational Semantics: *SEM (pronounced "starsem"). This time *SEM will be co-located with ACL 2017 in Vancouver (Canada), and it will take place August 3-4, 2017.

*SEM brings together researchers interested in the semantics of natural languages and its computational modeling. The conference embraces symbolic and probabilistic approaches, and everything in between; theoretical contributions as well as practical applications are welcome in the form of long and short papers. The long-term goal of *SEM is to provide a stable forum for the growing number of NLP researchers working on all aspects of semantics.

This year, the *SEM special theme is Representations of Meaning. See more details in the Call for Papers.

News: The 2018 edition of *SEM will be co-located with NAACL 2018!

Other topics of interest include, but are not limited to:

  • Formal approaches to semantics.

  • Lexical semantics.

  • Distributional semantics; data-driven semantics; mathematical methods for semantics.

  • Semantic parsing and interpretation; syntax-semantics interface.

  • Textual inference; entailment and question answering.

  • Frames and semantic role labeling.

  • Semantic ambiguity and underspecification; word sense disambiguation and induction.

  • Semantic annotation and evaluation.

  • Temporal entities and relations; extraction of events and causal and temporal relations

  • Entity linking; pronouns and coreference; single- and cross-document coreference

  • Discourse semantics; discourse structure and presupposition; extra-propositional aspects of meaning; dialogue; semantics-pragmatics interface.

  • Metaphor, irony, and figurative meaning; rhetorical relations.

  • Multiword and idiomatic expressions.

  • Generation and summarization.

  • Knowledge mining and acquisition; semantic web and ontologies; ontology learning and population.

  • Semantics in applications; semantics for social media; sentiment analysis.

  • Grounding; semantics in multimodal approaches.

  • Machine reading.