BibSonomy publications for /user/diego_ma/ambiguityFri Dec 14 02:49:32 CET 2007Stanford, CASemantic Ambiguity and UnderspecificationSemantic Ambiguity and Underspecification1996underspecification ambiguity Fri Dec 14 02:47:40 CET 2007Zussamenfassung Vortrag vom 19.01.1999Desambiguierung im {I}nformation {R}etrieval1999inf_retrieval ambiguity Fri Dec 14 02:47:11 CET 2007IrelandUL-CSIS-94-15Link Grammars and Structural Ambiguity: A Study of Technical Text1994ambiguity link_grammar Fri Dec 14 02:45:42 CET 2007Journal of Semantics123-179Dealing with Ambiguities by Underspecification: construction, representation and deduction101993ambiguity UDRT underspecification Fri Dec 14 02:45:17 CET 2007AugustDraft for internal use onlyInference Problems in {ExtrAns}: Quick Summary1999answer_extraction ambiguity logic Fri Dec 14 02:45:16 CET 2007JanuaryDraftAn Ambiguous Logic2000ambiguity logic Fri Dec 14 02:43:54 CET 2007ParisWorkshop on Representation and Treatment of Syntactic Ambiguity in Natural Language Processing21-24Dealing with Ambiguities in an Answer Extraction System2000ExtrAns ambiguity Fri Dec 14 02:42:19 CET 2007Lori Levi's homepage?Using Context in Machine Translation of Spoken LanguageXXXXambiguity context machine_translation Fri Dec 14 02:40:27 CET 2007Hillsdale (New Jersey), Hove and LondonText-Based Intelligent Systems: Current research and practice in information extraction and retrieval59-82Mixed-Depth Representations of Natural Language Text1992NLP ambiguity Fri Dec 14 02:40:22 CET 2007Journal of Natural Language Processing43-31Graph Branch Algorithm: An Optimum Tree Search Method for Scored Dependency Graph with Arc Co-occurrence Constraints132006graphs ambiguity DG Preference Dependency Grammar (PDG) is a framework for the morphological, syntactic and semantic analysis of natural language sentences, PDG gives packed shared data structures for emcompassing the various ambiguities in each levels of sentence analysis with preference scores and a method for calculating the most plausible interpretation of a sentence. This paper proposes the Graph Branch Algorithm for computing the optimum deptendenc tree ( the most plausible interpretation of a sentence) from a scored dependendency forest which is a packed shated data strucutre encompassing all possible dependency trees (interpretations) of a sentence. The graph branch algorithm adopts the branch and bound principle for managing arbitrary arc co-occurrence constraints including the single valence occupation constraint which is a basic semantic constraint in PDG. This paper also reports the espeiment using English texts showing the computational complexity and behavior of the graph branch algorithm.Fri Dec 14 02:40:21 CET 2007Computational Linguistics1103-120Structural Ambiguity and Lexical Relations191993ambiguity Fri Dec 14 02:39:14 CET 2007FebruaryCLAUS-113Automated Reasoning and Discourse Disambiguation2000logic ambiguity The performance of first-order automated reasoning systems has been steadily improving, stimulated in part by the availability of test suites of mathematical problems on which the systems can be tested, tuned and compared. But discourse understanding in Natural Language poses different inference problems than mathematics. In order to tailor automated reasoning systems to the needs of Natural Language understanding, similar test suites need to be developed. In this paper, we claim that several kinds of ambiguity in discourse can be resolved through automated reasoning checks for consistency, informativity, and minimality. Future test suites should therefore include problems of these sorts. The overall goal then is to characterise the range of inference problems that discourse understanding gives rise to and that test suites should include.Fri Dec 14 02:38:59 CET 2007BerlinLecture Notes in Artificial IntelligenceAutomatic Ambiguity Resolution in Natural Language Processing11711996ambiguity Fri Dec 14 02:38:31 CET 2007CS-R9616Ambiguity and Reasoning1996ambiguity In this paper, reasoning with ambiguous representations is explored in a formal way, with ambiguities at the level of propositions in propositional logic and predicate logic, and ambiguous representations of scopings in predicate logic as the main examples. First a version of propositional logic with propositional ambiguities is presented and a sequent axiomatization for it is given. This is then extended to predicate logic. Next, predicate logic with scope ambiguites is introduced and discussed, and again a sequent calculus for it is proposed. The conclusion connects the results to natural language semantics, and briefly compares them with existing logics of ambiguity. An appendix gives completeness proofs for our versions of ambiguous propositional and predicate logic.Fri Dec 14 02:35:53 CET 2007Austin, TXProceedings of the 2nd Conference on Applied Natural Language Processing235-242Localizing Expression of Ambiguity1988ambiguity Fri Dec 14 02:35:22 CET 2007Computational LinguisticsAvailable also at \myurl{http://www.cam.sri.com/tr/crc041/paper.ps.Z}4635-648Training and Scaling Preference Functions for Disambiguation201994ambiguity