*SEM 2017: THE SIXTH JOINT CONFERENCE ON LEXICAL AND COMPUTATIONAL SEMANTICSAugust 3-4 2017, Vancouver, CanadaCo-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 on the 3-4 of August 2017.
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.
Topics of interest include, but are not limited to:
Representations of meaning (special topic this year: see below).
Formal approaches to 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
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.