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  • 1.
    Kuhlmann, Marco
    Uppsala universitet, Institutionen för lingvistik och filologi.
    Mildly Non-Projective Dependency Grammar2013Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 39, nr 2, s. 355-387Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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 somewhat 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 on empirical data.

  • 2.
    Kuhlmann, Marco
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Koller, Alexander
    University of Potsdam, Germany.
    Satta, Giorgio
    University of Padua, Italy.
    Lexicalization and Generative Power in CCG2015Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 41, nr 2, s. 215-247Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The weak equivalence of Combinatory Categorial Grammar (CCG) and Tree-Adjoining Grammar (TAG) is a central result of the literature on mildly context-sensitive grammar formalisms. However, the categorial formalism for which this equivalence has been established differs significantly from the versions of CCG that are in use today. In particular, it allows restriction of combinatory rules on a per grammar basis, whereas modern CCG assumes a universal set of rules, isolating all cross-linguistic variation in the lexicon. In this article we investigate the formal significance of this difference. Our main result is that lexicalized versions of the classical CCG formalism are strictly less powerful than TAG.

  • 3.
    Kuhlmann, Marco
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Oepen, Stephan
    Department of Informatics, University of Oslo.
    Towards a Catalogue of Linguistic Graph Banks2016Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 42, nr 4, s. 819-827Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Graphs exceeding the formal complexity of rooted trees are of growing relevance to much NLP research. Although formally well understood in graph theory, there is substantial variation in the types of linguistic graphs, as well as in the interpretation of various structural properties. To provide a common terminology and transparent statistics across different collections of graphs in NLP, we propose to establish a shared community resource with an open-source reference implementation for common statistics.

  • 4.
    Kuhlmann, Marco
    et al.
    Uppsala universitet, Institutionen för lingvistik och filologi.
    Satta, Giorgio
    University of Padua, Padua, Italy.
    Tree-Adjoining Grammars are not Closed Under Strong Lexicalization2012Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 38, nr 3, s. 617-629Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A lexicalized tree-adjoining grammar is a tree-adjoining grammar where each elementary tree contains some overt lexical item. Such grammars are being used to give lexical accounts of syntactic phenomena, where an elementary tree defines the domain of locality of the syntactic and semantic dependencies of its lexical items. It has been claimed in the literature that for every tree-adjoining grammar, one can construct a strongly equivalent lexicalized version. We show that such a procedure does not exist: Tree-adjoining grammars are not closed under strong lexicalization.

  • 5.
    Kuhlmann, Marco
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Satta, Giorgio
    Univ Padua, Italy.
    Jonsson, Peter
    Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska fakulteten.
    On the Complexity of CCG Parsing2018Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 44, nr 3, s. 447-482Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We study the parsing complexity of Combinatory Categorial Grammar (CCG) in the formalism of Vijay-Shanker and Weir (1994). As our main result, we prove that any parsing algorithm for this formalism will take in the worst case exponential time when the size of the grammar, and not only the length of the input sentence, is included in the analysis. This sets the formalism of Vijay-Shanker and Weir (1994) apart from weakly equivalent formalisms such as Tree Adjoining Grammar, for which parsing can be performed in time polynomial in the combined size of grammar and input sentence. Our results contribute to a refined understanding of the class of mildly context-sensitive grammars, and inform the search for new, mildly context-sensitive versions of CCG.

  • 6.
    Stymne, Sara
    et al.
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Cancedda, Nicola
    Xerox Research Centre Europe.
    Ahrenberg, Lars
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Generation of Compound Words in Statistical Machine Translation into Compounding Languages2013Ingår i: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 39, nr 4, s. 1067-1108Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this article we investigate statistical machine translation (SMT) into Germanic languages, with a focus on compound processing. Our main goal is to enable the generation of novel compounds that have not been seen in the training data. We adopt a split-merge strategy, where compounds are split before training the SMT system, and merged after the translation step. This approach reduces sparsity in the training data, but runs the risk of placing translations of compound parts in non-consecutive positions. It also requires a postprocessing step of compound merging, where compounds are reconstructed in the translation output. We present a method for increasing the chances that components that should be merged are translated into contiguous positions and in the right order and show that it can lead to improvements both by direct inspection and in terms of standard translation evaluation metrics. We also propose several new methods for compound merging, based on heuristics and machine learning, which outperform previously suggested algorithms. These methods can produce novel compounds and a translation with at least the same overall quality as the baseline. For all subtasks we show that it is useful to include part-of-speech based information in the translation process, in order to handle compounds.

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