Parsing Weighted Order-Preserving Hyperedge Replacement Grammars

Björklund, Henrik; Drewes, Frank; Ericson, Petter

doi:10.18653/v1/w19-5701

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Through another set of syntactic restrictions on HRGs, Björklund et al [6], [5] arrive at orderpreserving dag grammars (OPDGs) -with or without weights -which can be parsed in linear time. Intuitively, the restrictions combine to ensure that each generated graph can be uniquely represented by a tree in a particular graph algebra.…”

Section: A Related Workmentioning

confidence: 99%

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Polynomial Graph Parsing with Non-Structural Reentrancies

Björklund,

Drewes,

Jonsson

2021

Preprint

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Graph-based semantic representations are valuable in natural language processing, where it is often simple and effective to represent linguistic concepts as nodes, and relations as edges between them. Several attempts has been made to find a generative device that is sufficiently powerful to represent languages of semantic graphs, while at the same allowing efficient parsing. We add to this line of work by introducing graph extension grammar, which consists of an algebra over graphs together with a regular tree grammar that generates expressions over the operations of the algebra. Due to the design of the operations, these grammars can generate graphs with non-structural reentrancies, a type of node-sharing that is excessively common in formalisms such as abstract meaning representation, but for which existing devices offer little support. We provide a parsing algorithm for graph extension grammars, which is proved to be correct and run in polynomial time.

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Section: A Related Workmentioning

confidence: 99%

“…This increases the flexibility with which it can attach to an existing structure. The operation was originally introduced to formalise the structure of object-oriented programs [17], and later adopted in computational linguistics [5].…”

Section: Definition 3 (Graph)mentioning

confidence: 99%

Polynomial Graph Parsing with Non-Structural Reentrancies

Björklund,

Drewes,

Jonsson

2021

Preprint

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Parsing Unranked Tree Languages, Folded Once

Berglund,

Björklund,

Björklund

2023

Lecture Notes in Computer Science

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Generation and Polynomial Parsing of Graph Languages with Non-Structural Reentrancies

Björklund

Drewes

Jönsson

2023

Computational Linguistics

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Graph-based semantic representations are popular in natural language processing (NLP), where it is often convenient to model linguistic concepts as nodes and relations as edges between them. Several attempts have been made to find a generative device that is sufficiently powerful to describe languages of semantic graphs, while at the same allowing efficient parsing. We contribute to this line of work by introducing graph extension grammar, a variant of the contextual hyperedge replacement grammars proposed by Hoffmann et al. Contextual hyperedge replacement can generate graphs with non-structural reentrancies, a type of node-sharing that is very common in formalisms such as abstract meaning representation, but which context-free types of graph grammars cannot model. To provide our formalism with a way to place reentrancies in a linguistically meaningful way, we endow rules with logical formulas in counting monadic second-order logic. We then present a parsing algorithm and show as our main result that this algorithm runs in polynomial time on graph languages generated by a subclass of our grammars, the so-called local graph extension grammars.

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Parsing Weighted Order-Preserving Hyperedge Replacement Grammars

Abstract: We introduce a weighted extension of the recently proposed notion of order-preserving hyperedge-replacement grammars and prove that the weight of a graph according to such a weighted graph grammar can be computed uniformly in quadratic time (under assumptions made precise in the paper).

Cited by 3 publications

References 14 publications

Polynomial Graph Parsing with Non-Structural Reentrancies

Polynomial Graph Parsing with Non-Structural Reentrancies

Parsing Unranked Tree Languages, Folded Once

Generation and Polynomial Parsing of Graph Languages with Non-Structural Reentrancies

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