2,667 research outputs found
Message-Passing Protocols for Real-World Parsing -- An Object-Oriented Model and its Preliminary Evaluation
We argue for a performance-based design of natural language grammars and
their associated parsers in order to meet the constraints imposed by real-world
NLP. Our approach incorporates declarative and procedural knowledge about
language and language use within an object-oriented specification framework. We
discuss several message-passing protocols for parsing and provide reasons for
sacrificing completeness of the parse in favor of efficiency based on a
preliminary empirical evaluation.Comment: 12 pages, uses epsfig.st
CHR as grammar formalism. A first report
Grammars written as Constraint Handling Rules (CHR) can be executed as
efficient and robust bottom-up parsers that provide a straightforward,
non-backtracking treatment of ambiguity. Abduction with integrity constraints
as well as other dynamic hypothesis generation techniques fit naturally into
such grammars and are exemplified for anaphora resolution, coordination and
text interpretation.Comment: 12 pages. Presented at ERCIM Workshop on Constraints, Prague, Czech
Republic, June 18-20, 200
Automatic acquisition of Spanish LFG resources from the Cast3LB treebank
In this paper, we describe the automatic annotation of the Cast3LB Treebank with LFG f-structures for the subsequent extraction of Spanish probabilistic grammar and lexical resources. We adapt the approach and methodology of Cahill et al. (2004), O’Donovan et al. (2004) and elsewhere for English to Spanish and the Cast3LB treebank encoding. We report on the quality and coverage of the automatic f-structure annotation. Following the pipeline and integrated models of Cahill et al. (2004), we extract wide-coverage
probabilistic LFG approximations and parse unseen Spanish text into f-structures. We also extend Bikel’s (2002) Multilingual Parse Engine to include a Spanish language module. Using the retrained Bikel parser in the pipeline model gives the best results against a manually constructed gold standard (73.20% predsonly f-score). We also extract Spanish lexical resources: 4090 semantic form types with 98 frame types. Subcategorised prepositions and particles are included in the frames
Automatic acquisition of LFG resources for German - as good as it gets
We present data-driven methods for the acquisition of LFG resources from two German treebanks. We discuss problems specific to semi-free word order languages as well as problems arising fromthe data structures determined
by the design of the different treebanks. We compare two ways of encoding semi-free word order, as done in the two German treebanks, and argue that the design of the TiGer treebank is more adequate for the acquisition of LFG
resources. Furthermore, we describe an architecture for LFG grammar acquisition for German, based on the two German treebanks, and compare our results with a hand-crafted German LFG grammar
Concurrent Lexicalized Dependency Parsing: The ParseTalk Model
A grammar model for concurrent, object-oriented natural language parsing is
introduced. Complete lexical distribution of grammatical knowledge is achieved
building upon the head-oriented notions of valency and dependency, while
inheritance mechanisms are used to capture lexical generalizations. The
underlying concurrent computation model relies upon the actor paradigm. We
consider message passing protocols for establishing dependency relations and
ambiguity handling.Comment: 90kB, 7pages Postscrip
Interaction Grammars
Interaction Grammar (IG) is a grammatical formalism based on the notion of
polarity. Polarities express the resource sensitivity of natural languages by
modelling the distinction between saturated and unsaturated syntactic
structures. Syntactic composition is represented as a chemical reaction guided
by the saturation of polarities. It is expressed in a model-theoretic framework
where grammars are constraint systems using the notion of tree description and
parsing appears as a process of building tree description models satisfying
criteria of saturation and minimality
Three New Probabilistic Models for Dependency Parsing: An Exploration
After presenting a novel O(n^3) parsing algorithm for dependency grammar, we
develop three contrasting ways to stochasticize it. We propose (a) a lexical
affinity model where words struggle to modify each other, (b) a sense tagging
model where words fluctuate randomly in their selectional preferences, and (c)
a generative model where the speaker fleshes out each word's syntactic and
conceptual structure without regard to the implications for the hearer. We also
give preliminary empirical results from evaluating the three models' parsing
performance on annotated Wall Street Journal training text (derived from the
Penn Treebank). In these results, the generative (i.e., top-down) model
performs significantly better than the others, and does about equally well at
assigning part-of-speech tags.Comment: 6 pages, LaTeX 2.09 packaged with 4 .eps files, also uses colap.sty
and acl.bs
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