Richard S. Crouch

Parsing the Wall Street Journal using a Lexical-Functional Grammar and Discriminative Estimation Techniques

We present a stochastic parsing system consisting of a Lexical-Functional Grammar (LFG), a constraint-based parser and a stochastic disambiguation model. We report on the results of applying this system to parsing the UPenn Wall Street Journal (WSJ) treebank. The model combines full and partial parsing techniques to reach full grammar coverage on unseen data. The treebank annotations are used to provide partially labeled data for discriminative statistical estimation using exponential models. Disambiguation performance is evaluated by measuring matches of predicate-argument relations on two distinct test sets. On a gold standard of manually annotated f-structures for a subset of the WSJ treebank, this evaluation reaches 79% F-score. An evaluation on a gold standard of dependency relations for Brown corpus data achieves 76% F-score.

MONOTONIC SEMANTIC INTERPRETATION

Aspects of semantic interpretation, such as quantifier scoping and reference resolution, are often realised computationally by non-monotonic operations involving loss of information and destructive manipulation of semantic representations. The paper describes how monotonic reference resolution and scoping can be carried out using a revised Quasi Logical Form (QLF) representation. Semantics for QLF are presented in which the denotations of formulas are extended monotonically as QLF expressions are resolved.

Statistical sentence condensation using ambiguity packing and stochastic disambiguation methods for Lexical-Functional Grammar

We present an application of ambiguity packing and stochastic disambiguation techniques for Lexical-Functional Grammars (LFG) to the domain of sentence condensation. Our system incorporates a linguistic parser/generator for LFG, a transfer component for parse reduction operating on packed parse forests, and a maximum-entropy model for stochastic output selection. Furthermore, we propose the use of standard parser evaluation methods for automatically evaluating the summarization quality of sentence condensation systems. An experimental evaluation of summarization quality shows a close correlation between the automatic parse-based evaluation and a manual evaluation of generated strings. Overall summarization quality of the proposed system is state-of-the-art, with guaranteed grammaticality of the system output due to the use of a constraint-based parser/generator.

Making ontologies work for resolving redundancies across documents

Producing normalized representations from different ways of expressing the same idea.

Deverbal Nouns in Knowledge Representation

Deverbal nouns pose serious challenges for knowledge-representation systems. We present a method of canonicalizing deverbal noun representations, relying on a rich lexicon of verb subcategorization frames, the WordNet database, a large finite-state network for derivational morphology and a series of heuristics for mapping deverbal arguments onto the arguments of corresponding verbs.1

Local Textual Inference: Can it be Defined or Circumscribed?

This paper argues that local textual inferences come in three well-defined varieties (entailments, conventional implicatures/presuppositions, and conversational implicatures) and one less clearly defined one, generally available world knowledge. Based on this taxonomy, it discusses some of the examples in the Pascal text suite and shows that these examples do not fall into any of them. It proposes to enlarge the test suite with examples that are more directly related to the inference patterns discussed.

Ellipsis and quantification: a substitutional approach

The paper describes a substitutional approach to ellipsis resolution giving comparable results to (Dalrymple et al., 1991), but without the need for order-sensitive interleaving of quantifier scoping and ellipsis resolution. It is argued that the order-independence results from viewing semantic interpretation as building a description of a semantic composition, instead of the more common view of interpretation as actually performing the composition.