@InProceedings{mcshane-nirenburg:2016:GramLex,
  author    = {McShane, Marjorie  and  Nirenburg, Sergei},
  title     = {Extra-Specific Multiword Expressions for Language-Endowed Intelligent Agents},
  booktitle = {Proceedings of the Workshop on Grammar and Lexicon: interactions and interfaces (GramLex)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {28--37},
  abstract  = {Language-endowed intelligent agents benefit from leveraging lexical knowledge
	falling at different points along a spectrum of compositionality. This means
	that robust computational lexicons should include not only the compositional
	expectations of argument-taking words, but also non-compositional collocations
	(idioms), semi-compositional collocations that might be difficult for an agent
	to interpret (e.g., standard metaphors), and even collocations that could be
	compositionally analyzed but are so frequently encountered that recording their
	meaning increases the efficiency of interpretation. In this paper we argue that
	yet another type of string-to-meaning mapping can also be useful to intelligent
	agents: remembered semantic analyses of actual text inputs. These can be viewed
	as super-specific multi-word expressions whose recorded interpretations mimic a
	person’s memories of knowledge previously learned from language input. These
	differ from typical annotated corpora in two ways. First, they provide a full,
	context-sensitive semantic interpretation rather than select features. Second,
	they are are formulated in the ontologically-grounded metalanguage used in a
	particular agent environment, meaning that the interpretations contribute to
	the dynamically evolving cognitive capabilites of agents configured in that
	environment.},
  url       = {http://aclweb.org/anthology/W16-3805}
}