Marco Kuhlmann

Mildly Non-Projective Dependency Structures

Syntactic parsing requires a fine balance between expressivity and complexity, so that naturally occurring structures can be accurately parsed without compromising efficiency. In dependency-based parsing, several constraints have been proposed that restrict the class of permissible structures, such as projectivity, planarity, multi-planarity, well-nestedness, gap degree, and edge degree. While projectivity is generally taken to be too restrictive for natural language syntax, it is not clear which of the other proposals strikes the best balance between expressivity and complexity. In this paper, we review and compare the different constraints theoretically, and provide an experimental evaluation using data from two treebanks, investigating how large a proportion of the structures found in the treebanks are permitted under different constraints. The results indicate that a combination of the well-nestedness constraint and a parametric constraint on discontinuity gives a very good fit with the linguistic data.

SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing

Task 18 at SemEval 2015 defines Broad-Coverage Semantic Dependency Parsing (SDP) as the problem of recovering sentence-internal predicate–argument relationships for all content words, i.e. the sema ...

Treebank Grammar Techniques for Non-Projective Dependency Parsing

An open problem in dependency parsing is the accurate and efficient treatment of non-projective structures. We propose to attack this problem using chart-parsing algorithms developed for mildly context-sensitive grammar formalisms. In this paper, we provide two key tools for this approach. First, we show how to reduce non-projective dependency parsing to parsing with Linear Context-Free Rewriting Systems (LCFRS), by presenting a technique for extracting LCFRS from dependency treebanks. For efficient parsing, the extracted grammars need to be transformed in order to minimize the number of nonterminal symbols per production. Our second contribution is an algorithm that computes this transformation for a large, empirically relevant class of grammars.

An Improved Oracle for Dependency Parsing with Online Reordering

We present an improved training strategy for dependency parsers that use online reordering to handle non-projective trees. The new strategy improves both efficiency and accuracy by reducing the number of swap operations performed on non-projective trees by up to 80%. We present state-of-the-art results for five languages with the best ever reported results for Czech.

A relational syntax-semantics interface based on dependency grammar

We propose a syntax-semantics interface that realises the mapping between syntax and semantics as a relation and does not make functionality assumptions in either direction. This interface is stated in terms of Extensible Dependency Grammar (XDG), a grammar formalism we newly specify. XDGs constraint-based parser supports the concurrent flow of information between any two levels of linguistic representation, even when only partial analyses are available. This generalises the concept of underspecification.

Optimal Reduction of Rule Length in Linear Context-Free Rewriting Systems

Linear Context-free Rewriting Systems (LCFRS) is an expressive grammar formalism with applications in syntax-based machine translation. The parsing complexity of an LCFRS is exponential in both the rank of a production, defined as the number of nonterminals on its right-hand side, and a measure for the discontinuity of a phrase, called fan-out. In this paper, we present an algorithm that transforms an LCFRS into a strongly equivalent form in which all productions have rank at most 2, and has minimal fan-out. Our results generalize previous work on Synchronous Context-Free Grammar, and are particularly relevant for machine translation from or to languages that require syntactic analyses with discontinuous constituents.

Mildly non-projective dependency grammar

Syntactic representations based on word-to-word dependencies have a long-standing tradition in descriptive linguistics, and receive considerable interest in many applications. Nevertheless, dependency syntax has remained something of an island from a formal point of view. Moreover, most formalisms available for dependency grammar are restricted to projective analyses, and thus not able to support natural accounts of phenomena such as wh-movement and cross–serial dependencies. In this article we present a formalism for non-projective dependency grammar in the framework of linear context-free rewriting systems. A characteristic property of our formalism is a close correspondence between the non-projectivity of the dependency trees admitted by a grammar on the one hand, and the parsing complexity of the grammar on the other. We show that parsing with unrestricted grammars is intractable. We therefore study two constraints on non-projectivity, block-degree and well-nestedness. Jointly, these two constraints define a class of “mildly” non-projective dependency grammars that can be parsed in polynomial time. An evaluation on five dependency treebanks shows that these grammars have a good coverage of empirical data.

Dependency Structures and Lexicalized Grammars : An Algebraic Approach

Preliminaries.- Projective Dependency Structures.- Dependency Structures of Bounded Degree.- Dependency Structures without Crossings.- Structures and Grammars.- Regular Dependency Languages.- Generative Capacity and Parsing Complexity.- Conclusion.

Dependency Grammar: Classification and Exploration

Syntactic representations based on word-to-word dependencies have a long tradition in descriptive linguistics [29]. In recent years, they have also become increasingly used in computational tasks, such as information extraction [5], machine translation [43], and parsing [42]. Among the purported advantages of dependency over phrase structure representations are conciseness, intuitive appeal, and closeness to semantic representations such as predicate-argument structures. On the more practical side, dependency representations are attractive due to the increasing availability of large corpora of dependency analyses, such as the Prague Dependency Treebank [19].

Dependency Trees and the Strong Generative Capacity of CCG

We propose a novel algorithm for extracting dependencies from the derivations of a large fragment of CCG. Unlike earlier proposals, our dependency structures are always tree-shaped. We then use these dependency trees to compare the strong generative capacities of CCG and TAG and obtain surprising results: Both formalisms generate the same languages of derivation trees --- but the mechanisms they use to bring the words in these trees into a linear order are incomparable.