Type-driven semantic interpretation and feature dependencies in R-LFG

Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constraints fall out as a by-product of the linear logic machinery they propose for semantic interpretation, thus making those f-structure mechanisms redundant. Given that linear logic machinery or something like it is independently needed for semantic interpretation, it seems reasonable to explore the extent to which it is capable of handling feature structure constraints as well. R-LFG represents the extreme position that all linguistically required feature structure dependencies can be captured by the resource-accounting machinery of a linear or similiar logic independently needed for semantic interpretation, making LFG's unification machinery redundant. The goal is to show that LFG linguistic analyses can be expressed as clearly and perspicuously using the smaller set of mechanisms of R-LFG as they can using the much larger set of unification-based mechanisms in LFG: if this is the case then we will have shown that positing these extra f-structure mechanisms is not linguistically warranted.Comment: 30 pages, to appear in the the ``Glue Language'' volume edited by Dalrymple, uses tree-dvips, ipa, epic, eepic, fullnam

From treebank resources to LFG F-structures

We present two methods for automatically annotating treebank resources with functional structures. Both methods define systematic patterns of correspondence between partial PS configurations and functional structures. These are applied to PS rules extracted from treebanks, or directly to constraint set encodings of treebank PS trees

Treebank-based acquisition of LFG resources for Chinese

This paper presents a method to automatically acquire wide-coverage, robust, probabilistic Lexical-Functional Grammar resources for Chinese from the Penn Chinese Treebank (CTB). Our starting point is the earlier, proofof- concept work of (Burke et al., 2004) on automatic f-structure annotation, LFG grammar acquisition and parsing for Chinese using the CTB version 2 (CTB2). We substantially extend and improve on this earlier research as regards coverage, robustness, quality and fine-grainedness of the resulting LFG resources. We achieve this through (i) improved LFG analyses for a number of core Chinese phenomena; (ii) a new automatic f-structure annotation architecture which involves an intermediate dependency representation; (iii) scaling the approach from 4.1K trees in CTB2 to 18.8K trees in CTB version 5.1 (CTB5.1) and (iv) developing a novel treebank-based approach to recovering non-local dependencies (NLDs) for Chinese parser output. Against a new 200-sentence good standard of manually constructed f-structures, the method achieves 96.00% f-score for f-structures automatically generated for the original CTB trees and 80.01%for NLD-recovered f-structures generated for the trees output by Bikel’s parser

Phobos: A front-end approach to extensible compilers (long version)

This paper describes a practical approach for implementing certain types of domain-specific languages with extensible compilers. Given a compiler with one or more front-end languages, we introduce the idea of a "generic" front-end that allows the syntactic and semantic specification of domain-specific languages. Phobos, our generic front-end, offers modular language specification, allowing the programmer to define new syntax and semantics incrementally

Generative grammar

Generative Grammar is the label of the most influential research program in linguistics and related fields in the second half of the 20. century. Initiated by a short book, Noam Chomsky's Syntactic Structures (1957), it became one of the driving forces among the disciplines jointly called the cognitive sciences. The term generative grammar refers to an explicit, formal characterization of the (largely implicit) knowledge determining the formal aspect of all kinds of language behavior. The program had a strong mentalist orientation right from the beginning, documented e.g. in a fundamental critique of Skinner's Verbal behavior (1957) by Chomsky (1959), arguing that behaviorist stimulus-response-theories could in no way account for the complexities of ordinary language use. The "Generative Enterprise", as the program was called in 1982, went through a number of stages, each of which was accompanied by discussions of specific problems and consequences within the narrower domain of linguistics as well as the wider range of related fields, such as ontogenetic development, psychology of language use, or biological evolution. Four stages of the Generative Enterprise can be marked off for expository purposes

Treebank-based acquisition of a Chinese lexical-functional grammar

Scaling wide-coverage, constraint-based grammars such as Lexical-Functional Grammars (LFG) (Kaplan and Bresnan, 1982; Bresnan, 2001) or Head-Driven Phrase Structure Grammars (HPSG) (Pollard and Sag, 1994) from fragments to naturally occurring unrestricted text is knowledge-intensive, time-consuming and (often prohibitively) expensive. A number of researchers have recently presented methods to automatically acquire wide-coverage, probabilistic constraint-based grammatical resources from treebanks (Cahill et al., 2002, Cahill et al., 2003; Cahill et al., 2004; Miyao et al., 2003; Miyao et al., 2004; Hockenmaier and Steedman, 2002; Hockenmaier, 2003), addressing the knowledge acquisition bottleneck in constraint-based grammar development. Research to date has concentrated on English and German. In this paper we report on an experiment to induce wide-coverage, probabilistic LFG grammatical and lexical resources for Chinese from the Penn Chinese Treebank (CTB) (Xue et al., 2002) based on an automatic f-structure annotation algorithm. Currently 96.751% of the CTB trees receive a single, covering and connected f-structure, 0.112% do not receive an f-structure due to feature clashes, while 3.137% are associated with multiple f-structure fragments. From the f-structure-annotated CTB we extract a total of 12975 lexical entries with 20 distinct subcategorisation frame types. Of these 3436 are verbal entries with a total of 11 different frame types. We extract a number of PCFG-based LFG approximations. Currently our best automatically induced grammars achieve an f-score of 81.57% against the trees in unseen articles 301-325; 86.06% f-score (all grammatical functions) and 73.98% (preds-only) against the dependencies derived from the f-structures automatically generated for the original trees in 301-325 and 82.79% (all grammatical functions) and 67.74% (preds-only) against the dependencies derived from the manually annotated gold-standard f-structures for 50 trees randomly selected from articles 301-325

TuLiPA : towards a multi-formalism parsing environment for grammar engineering

In this paper, we present an open-source parsing environment (Tübingen Linguistic Parsing Architecture, TuLiPA) which uses Range Concatenation Grammar (RCG) as a pivot formalism, thus opening the way to the parsing of several mildly context-sensitive formalisms. This environment currently supports tree-based grammars (namely Tree-Adjoining Grammars (TAG) and Multi-Component Tree-Adjoining Grammars with Tree Tuples (TT-MCTAG)) and allows computation not only of syntactic structures, but also of the corresponding semantic representations. It is used for the development of a tree-based grammar for German