Marjorie McShane


2016

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Detection and Resolution of Verb Phrase Ellipsis
Marjorie McShane | Petr Babkin
Linguistic Issues in Language Technology, Volume 13, 2016

Verb phrase (VP) ellipsis is the omission of a verb phrase whose meaning can be reconstructed from the linguistic or real-world context. It is licensed in English by auxiliary verbs, often modal auxiliaries: She can go to Hawaii but he can’t [e]. This paper describes a system called ViPER (VP Ellipsis Resolver) that detects and resolves VP ellipsis, relying on linguistic principles such as syntactic parallelism, modality correlations, and the delineation of core vs. peripheral sentence constituents. The key insight guiding the work is that not all cases of ellipsis are equally difficult: some can be detected and resolved with high confidence even before we are able to build systems with human-level semantic and pragmatic understanding of text.

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Extra-Specific Multiword Expressions for Language-Endowed Intelligent Agents
Marjorie McShane | Sergei Nirenburg
Proceedings of the Workshop on Grammar and Lexicon: interactions and interfaces (GramLex)

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.

2014

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Nominal Compound Interpretation by Intelligent Agents
Marjorie McShane | Stephen Beale | Petr Babkin
Linguistic Issues in Language Technology, Volume 10, 2014

This paper presents a cognitively-inspired algorithm for the semantic analysis of nominal compounds by intelligent agents. The agents, modeled within the OntoAgent environment, are tasked to compute a full context-sensitive semantic interpretation of each compound using a battery of engines that rely on a high-quality computational lexicon and ontology. Rather than being treated as an isolated “task”, as in many NLP approaches, nominal compound analysis in OntoAgent represents a minimal extension to the core process of semantic analysis. We hypothesize that seeking similarities across language analysis tasks reflects the spirit of how people approach language interpretation, and that this approach will make feasible the long-term development of truly sophisticated, human-like intelligent agents. The initial evaluation of our approach to nominal compounds are fixed expressions, requiring individual semantic specification at the lexical level.

2008

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Language Understanding in Maryland Virtual Patient
Sergei Nirenburg | Stephen Beale | Marjorie McShane | Bruce Jarrell | George Fantry
Coling 2008: Proceedings of the workshop on Speech Processing for Safety Critical Translation and Pervasive Applications

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The Idiom–Reference Connection
Marjorie McShane | Sergei Nirenburg
Semantics in Text Processing. STEP 2008 Conference Proceedings

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Resolving Paraphrases to Support Modeling Language Perception in an Intelligent Agent
Sergei Nirenburg | Marjorie McShane | Stephen Beale
Semantics in Text Processing. STEP 2008 Conference Proceedings

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Baseline Evaluation of WSD and Semantic Dependency in OntoSem
Sergei Nirenburg | Stephen Beale | Marjorie McShane
Semantics in Text Processing. STEP 2008 Conference Proceedings

2007

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Briefly Noted: Lingvisticeskie problemy komp’juternoj morfologii [Linguistic Issues in Computational Morphology], by S. A. Koval’
Marjorie McShane
Computational Linguistics, Volume 33, Number 2, June 2007

2005

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Increasing Understanding: Interpreting Events of Change
Sergei Nirenburg | Marjorie McShane | Stephen Beale
Proceedings of OntoLex 2005 - Ontologies and Lexical Resources

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Semantically Rich Human-Aided Machine Annotation
Marjorie McShane | Sergei Nirenburg | Stephen Beale | Thomas O’Hara
Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky

2004

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The Rationale for Building an Ontology Expressly for NLP
Sergei Nirenburg | Marjorie McShane | Stephen Beale
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Some Meaning Procedures of Ontological Semantics
Marjorie McShane | Stephen Beale | Sergei Nirenburg
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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OntoSem and SIMPLE: Two multi-lingual world views
Marjorie McShane | Margalit Zabludowski | Sergei Nirenburg | Stephen Beale
Proceedings of the 2nd Workshop on Text Meaning and Interpretation

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Evaluating the performance of the OntoSem semantic analyzer
Sergei Nirenburg | Stephen Beale | Marjorie McShane
Proceedings of the 2nd Workshop on Text Meaning and Interpretation

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Question answering using ontological semantics
Stephen Beale | Benoit Lavoie | Marjorie McShane | Sergei Nirenburg | Tanya Korelsky
Proceedings of the 2nd Workshop on Text Meaning and Interpretation

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OntoSem Methods for Processing Semantic Ellipsis
Marjorie McShane | Stephen Beale | Sergei Nirenburg
Proceedings of the Computational Lexical Semantics Workshop at HLT-NAACL 2004

2003

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Operative strategies in ontological semantics
Sergei Nirenburg | Marjorie McShane | Stephen Beale
Proceedings of the HLT-NAACL 2003 Workshop on Text Meaning

2001

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Bootstrapping Morphological Analyzers by Combining Human Elicitation and Machine Learning
Kemal Oflazer | Sergei Nirenberg | Marjorie McShane
Computational Linguistics, Volume 27, Number 1, March 2001