Her scientific interests lie mostly in Artificial intelligence, Natural language processing, Annotation, Treebank and Verb. Martha Palmer combines topics linked to Information retrieval with her work on Artificial intelligence. Her research integrates issues of Speech recognition and SemEval in her study of Natural language processing.
The concepts of her Annotation study are interwoven with issues in Relational database and Representation. Her Treebank study combines topics in areas such as Natural language understanding, Dependency grammar, Phrase and Lexical database. Her Verb study combines topics from a wide range of disciplines, such as Lexical density, WordNet, Lexicon, Polysemy and Syntax.
Her main research concerns Artificial intelligence, Natural language processing, Verb, Annotation and Semantic role labeling. Her study in PropBank, VerbNet, Semantics, Lexicon and Natural language is carried out as part of her Artificial intelligence studies. Her PropBank research incorporates elements of Light verb and Proposition.
Martha Palmer frequently studies issues relating to Information retrieval and Natural language processing. Her study in Verb is interdisciplinary in nature, drawing from both Sentence, WordNet, Polysemy and Cluster analysis. The Syntax study combines topics in areas such as Grammar and Rule-based machine translation.
Her primary scientific interests are in Artificial intelligence, Natural language processing, Annotation, Verb and PropBank. The concepts of her Artificial intelligence study are interwoven with issues in Domain and Identification. Her Natural language processing research is multidisciplinary, relying on both Semantics, Information retrieval and Coreference.
Her biological study spans a wide range of topics, including Leverage, Relation, Schema, Data science and Conceptualization. Her Verb research integrates issues from Topic model, Speech recognition, Cluster analysis, Adjective and Lexicon. Martha Palmer combines subjects such as Proposition, Classifier, WordNet, Unification and Predicate with her study of PropBank.
Martha Palmer mainly investigates Artificial intelligence, Natural language processing, Annotation, Coreference and Information retrieval. When carried out as part of a general Artificial intelligence research project, her work on Deep learning and SemEval is frequently linked to work in Natural disaster, Geospatial analysis and Timeline, therefore connecting diverse disciplines of study. Her work on Treebank, Parsing and PropBank as part of general Natural language processing research is frequently linked to Empirical research, thereby connecting diverse disciplines of science.
Her Annotation research is multidisciplinary, incorporating elements of Scheme, Variety and Social media. Her Coreference research incorporates themes from Semantics and Information extraction. Her studies in Information retrieval integrate themes in fields like Domain, FrameNet and Manual annotation.
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VERB SEMANTICS AND LEXICAL SELECTION
Zhibiao Wu;Martha Palmer.
meeting of the association for computational linguistics (1994)
The Proposition Bank: An Annotated Corpus of Semantic Roles
Martha Palmer;Daniel Gildea;Paul Kingsbury.
Computational Linguistics (2005)
Abstract Meaning Representation for Sembanking
Laura Banarescu;Claire Bonial;Shu Cai;Madalina Georgescu.
linguistic annotation workshop (2013)
OntoNotes: The 90% Solution
Eduard Hovy;Mitchell Marcus;Martha Palmer;Lance Ramshaw.
north american chapter of the association for computational linguistics (2006)
Verbnet: a broad-coverage, comprehensive verb lexicon
Karin Kipper Schuler;Martha S. Palmer.
From treebank to propbank
Paul R. Kingsbury;Martha Palmer.
language resources and evaluation (2002)
Class-Based Construction of a Verb Lexicon
Karin Kipper;Hoa Trang Dang;Martha Palmer.
national conference on artificial intelligence (2000)
A large-scale classification of English verbs
Karin Kipper;Anna Korhonen;Neville Ryant;Martha Palmer.
language resources and evaluation (2008)
A vision for technology-mediated support for public participation & assistance in mass emergencies & disasters
Leysia Palen;Kenneth M. Anderson;Gloria Mark;James Martin.
Calibrating Features for Semantic Role Labeling
Nianwen Xue;Martha Palmer.
empirical methods in natural language processing (2004)
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