lnu.sePublications
Change search
Refine search result
1 - 23 of 23
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    CoNLL-X SharedTask: Multi-lingual Dependency Parsing2006Report (Other academic)
    Abstract [en]

    The goal of this report is to summarize our experiments and present the final result of our participation in the CoNLL-X Shared Task 2006. The topic of this year's shared task was multi-lingual dependency parsing.

    The organizers have prepared 13 existing dependency treebanks so that they all comply to the same markup format. The training and test data for the languages differ in size, granularity and quality, but they have tried to even out differences in the markup format. No additional information is allowed to be used besides the provided training data, forcing the parser to be fully automatic and data-driven. Ideally, the same parser should be trainable for all languages, possibly by adjusting parameters.

    The main goal is to assign labeled dependency structure for all languages on held out test data, approximately 5 000 tokens for each language. The main metric for comparison of the different parsers of the participants is therefore labeled attachment score.

  • 2.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Converting Dependency Treebanks to MALT-XML2005Report (Other academic)
    Abstract [en]

    In data-driven approaches to natural language processing, a common problem is the lack of data for many languages. Within the project Stochastic Dependency Grammars for Natural Language Parsing at Växjö University, we (Joakim Nivre, Johan Hall and Jens Nilsson) are developing a deterministic data-driven dependency parser, which is language independent. In this project we intend to enlarge the data resources for our parser. For the moment, we have only tested our parser on small Swedish treebank converted to dependency structure, and on English using Penn Treebank converted to dependency trees. Since we do not have more Swedish dependency treebanks at hand, we want to broaden our view towards treebanks for other languages, especially the bigger ones, to investigate the influence of data size. Primarily, we are focusing on the Danish Dependency Treebank (DDT) and the Prague Dependency Treebank (PDT). These treebanks are not in a format that we can use for our parser and therefore we have to convert them to MALT-XML, a format which our parser can handle.

  • 3.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nilsson, Jens
    Nivre, Joakim
    Single Malt or Blended? A Study in Multilingual Parser OptimizationManuscript (preprint) (Other (popular science, discussion, etc.))
  • 4.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Eryigit, Gülsen
    Megyesi, Béata
    Nilsson, Mattias
    Saers, Markus
    Single Malt or Blended? A Study in Multilingual Parser Optimization2007In: Proceedings of the CoNLL Shared Task Session of EMNLP-CoNLL 2007, Association for Computational Linguistics , 2007, p. 933–939-Conference paper (Refereed)
    Abstract [en]

    We describe a two-stage optimization of the MaltParser system for the ten languages in the multilingual track of the CoNLL 2007 shared task on dependency parsing. The first stage consists in tuning a single-parser system for each language by optimizing parameters of the parsing algorithm, the feature model, and the learning algorithm. The second stage consists in building an ensemble system that combines six different parsing strategies, extrapolating from the optimal parameters settings for each language. When evaluated on the official test sets, the ensemble system significantly outperforms the single-parser system and achieves the highest average labeled attachment score.

  • 5.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    A Hybrid Constituency-Dependency Parser for Swedish2007In: Proceedings of the 16th Nordic Conference of Computational Linguistics (NODALIDA), 2007, p. 284–287-Conference paper (Refereed)
    Abstract [en]

    We present a data-driven parser that derives both constituent structures and dependency structures, alone or in combination, in one

    and the same process. When trained and tested on data from the Swedish treebank Talbanken05, the parser achieves a labeled dependency accuracy of 82% and a labeled bracketing F-score of 75%.

  • 6.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nivre, Joakim
    Nilsson, Jens
    Discriminative Classifiers for Deterministic Dependency ParsingManuscript (preprint) (Other (popular science, discussion, etc.))
  • 7.
    Hall, Johan
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Discriminative Classifiers for Deterministic Dependency Parsing2006In: Proceedings of the 44rd Annual Meeting of the Association for Computational Linguistics and 21th International Conference on Computational Linguistics (COLING-ACL 2006), July 17-21, 2006, Sydney, Australia, Association for Computational Linguistics, Stroudsburg , 2006, p. 316-323Conference paper (Refereed)
    Abstract [en]

    Deterministic parsing guided by treebankinduced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systematic comparison of memory-based learning (MBL) and support vector machines (SVM) for inducing classifiers for deterministic dependency parsing, using data from Chinese, English and Swedish, together with a variety of different feature models. The comparison shows that SVM gives higher accuracy for richly articulated feature models across all languages, albeit with considerably longer training times. The results also confirm that classifier-based deterministic parsing can achieve parsing accuracy very close to the best results reported for more complex parsing models.

  • 8.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Transformation and Combination in Data-Driven Dependency Parcing2009Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis deals with automatic syntactic analysis of natural languagetext, also known as parsing. The parsing approach is data-driven, whichmeans that parsers are constructed by means of machine learning, lookingat training data in the form of annotated natural language sentences. The syntactic framework used in the thesis is dependency-based. Robustness is one of the characteristics of the data-driven approaches investigated here.The overall aim of this thesis is to maintain robustness while increasing accuracy.The content of the thesis falls naturally into two tracks, a transformation track and a combination track. The  rst type of transformation investigatedis called pseudo-projective, because it enables strictly projective dependency parsers to recover non-projective dependency relations. Informally,a non-projective dependency tree contains crossing binary directed relations, when drawn above the sentence. Experimental results show that pseudo-projective transformations can improve accuracy significantly for a range of languages. The second type of transformation aims to facilitate the processing of specific linguistic constructions such as coordination and verb groups. Experimental results again show a positive effect on parsing accuracy for several languages, often greater than for the pseudo-projective transformations. However, the improvement of the transformations dependson the internal structure of the base parser, which is not the case for thepseudo-projective transformations. The combination track compares various approaches for combining data driven dependency parsers, again as a means of improving accuracy. As different parsers have different strengths and weaknesses, making parsers collaborate in order to  nd one single syntactic analysis may result in higher accuracy than any of the syntactic analyzers can produce by itself. The experimental results show that accuracy improves across languages, giventhat appropriate parsers are combined. The thesis ends with an attempt to combine the two tracks, showing that combining parsers with different tree transformations also increases accuracy. Moreover, this experiment indicates that high diversity among a small set of parsers is much more important than a large number of parsers with low diversity.

  • 9.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Tree Transformations in Inductive Dependency Parsing2007Licentiate thesis, monograph (Other academic)
    Abstract [en]

    This licentiate thesis deals with automatic syntactic analysis, or parsing, of natural languages. A parser constructs the syntactic analysis, which it learns by looking at correctly analyzed sentences, known as training data. The general topic concerns manipulations of the training data in order to improve the parsing accuracy.

    Several studies using constituency-based theories for natural languages in such automatic and data-driven syntactic parsing have shown that training data, annotated according to a linguistic theory, often needs to be adapted in various ways in order to achieve an adequate, automatic analysis. A linguistically sound constituent structure is not necessarily well-suited for learning and parsing using existing data-driven methods. Modifications to the constituency-based trees in the training data, and corresponding modifications to the parser output, have successfully been applied to increase the parser accuracy. The topic of this thesis is to investigate whether similar modifications in the form of tree transformations to training data, annotated with dependency-based structures, can improve accuracy for data-driven dependency parsers. In order to do this, two types of tree transformations are in focus in this thesis.

    %This is a topic that so far has been less studied.

    The first one concerns non-projectivity. The full potential of dependency parsing can only be realized if non-projective constructions are allowed, which pose a problem for projective dependency parsers. On the other hand, non-projective parsers tend, among other things, to be slower. In order to maintain the benefits of projective parsing, a tree transformation technique to recover non-projectivity while using a projective parser is presented here.

    The second type of transformation concerns linguistic phenomena that are possible but hard for a parser to learn, given a certain choice of dependency analysis. This study has concentrated on two such phenomena, coordination and verb groups, for which tree transformations are applied in order to improve parsing accuracy, in case the original structure does not coincide with a structure that is easy to learn.

    Empirical evaluations are performed using treebank data from various languages, and using more than one dependency parser. The results show that the benefit of these tree transformations used in preprocessing and postprocessing to a large extent is language, treebank and parser independent.

  • 10.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Tree Transformations in Inductive Dependency Parsing2007Licentiate thesis, monograph (Other academic)
    Abstract [en]

    This licentiate thesis deals with automatic syntactic analysis, or parsing, of natural languages. A parser constructs the syntactic analysis, which it learns by looking at correctly analyzed sentences, known as training data. The general topic concerns manipulations of the training data in order to improve the parsing accuracy.

    Several studies using constituency-based theories for natural languages in such automatic and data-driven syntactic parsing have shown that training data, annotated according to a linguistic theory, often needs to be adapted in various ways in order to achieve an adequate, automatic analysis. A linguistically sound constituent structure is not necessarily well-suited for learning and parsing using existing data-driven methods. Modifications to the constituency-based trees in the training data, and corresponding modifications to the parser output, have successfully been applied to increase the parser accuracy. The topic of this thesis is to investigate whether similar modifications in the form of tree transformations to training data, annotated with dependency-based structures, can improve accuracy for data-driven dependency parsers. In order to do this, two types of tree transformations are in focus in this thesis.

    The first one concerns non-projectivity. The full potential of dependency parsing can only be realized if non-projective constructions are allowed, which pose a problem for projective dependency parsers. On the other hand, non-projective parsers tend, among other things, to be slower. In order to maintain the benefits of projective parsing, a tree transformation technique to recover non-projectivity while using a projective parser is presented here.

    The second type of transformation concerns linguistic phenomena that are possible but hard for a parser to learn, given a certain choice of dependency analysis. This study has concentrated on two such phenomena, coordination and verb groups, for which tree transformations are applied in order to improve parsing accuracy, in case the original structure does not coincide with a structure that is easy to learn.

    Empirical evaluations are performed using treebank data from various languages, and using more than one dependency parser. The results show that the benefit of these tree transformations used in preprocessing and postprocessing to a large extent is language, treebank and parser independent.

  • 11.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Reconstruction of the Swedish Treebank Talbanken.2005Report (Other academic)
    Abstract [en]

    Data-driven parsing techniques have a number of advantages over rule-based parsing techniques, such as fast development time, broad-coverage and robustness. Treebanks, collections of syntactically annotated sentences, are important resources for data-driven parsers. When developing a parser for Swedish one needs a treebank containing Swedish sentences, but currently there is a lack of Swedish treebanks of substantial size. This holds for the other Nordic languages too, with Danish as an exception. The absence of Swedish treebanks is remarkable considering that two corpora of Swedish text augmented with syntactic annotation have been created, one as early as 1974 named Talbanken (Einarsson 1976), and another in the 80's named Syntag (Järborg 1980). Unfortunately, the annotation formats of these resources make them cumbersome to use for modern treebank tools and parsers. In a way, Sweden can be regarded as a pioneer in this area, but thereafter the work with creating new treebanks has decreased considerably.

  • 12.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    MAMBA Meets TIGER: Reconstructing a Swedish Treebank from Antiquity2005In: Proceedings from the special session on treebanks at NODALIDA 2005, Samfundslitteratur Press , 2005, p. 119-132Conference paper (Refereed)
    Abstract [en]

    In this paper, we will give an overview of the reconstruction process

    of the Swedish treebank Talbanken, created in the first half

    of the 70’s. Talbanken contains both written and spoken material,

    both encoded in the MAMBA-format. The goal has been

    to construct two new versions of the original data, one based

    on phrase structure and one on dependency structure. The outcome

    of the reconstruction, i.e. different versions of Talbanken,

    is available for non-commercial research and educational purposes.

  • 13.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Dependency Parsing by Transformation and Combination2008In: 6th International Conference on Natural Language Processing, GoTAL 2008, Springer, Gothenburg, Sweden , 2008, p. 348–359-Conference paper (Refereed)
    Abstract [en]

    This study presents new language and treebank independent

    graph transformations that improve accuracy in data-driven dependency parsing. We show that individual generic graph transformations can increase accuracy across treebanks, but especially when they are combined using established parser combination techniques. The combination experiments also indicate that the presumed best way to combine parsers, using the highest scoring parsers, is not necessarily the best approach.

  • 14.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    MaltEval: An Evaluation and Visualization Tool for Dependency Parsing2008In: Proceedings of the Sixth International Language Resources and Evaluation (LREC'08), Marrakech, Morocco , 2008Conference paper (Refereed)
    Abstract [en]

    This paper presents a freely available evaluation tool for dependency parsing, MaltEval (http://w3.msi.vxu.se/users/jni/malteval). It is flexible and extensible, and provides functionality for both quantitative evaluation and visualization of dependency structure. The quantitative evaluation is compatible with other standard evaluation software for dependency structure which does not produce visualization of dependency structure, and can output more details as well as new types of evaluation metrics. In addition, MaltEval has generic support for confusion matrices. It can also produce statistical significance tests when more than one parsed file is specified. The visualization

    module also has the ability to highlight discrepancies between the gold-standard files and the parsed files, and it comes with an easy to use GUI functionality to search in the dependency structure of the input files.

  • 15.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Generalizing Tree Transformations for Inductive Dependency Parsing2007In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, Association for Computational Linguistics , 2007, p. 968–975-Conference paper (Refereed)
    Abstract [en]

    Previous studies in data-driven dependency parsing have shown that tree transformations can improve parsing accuracy for specific parsers and data sets. We investigate to what extent this can be generalized across languages/treebanks and parsers, focusing on pseudo-projective parsing, as a way of capturing non-projective dependencies, and transformations used to facilitate parsing of coordinate structures and verb groups. The results indicate that the beneficial effect of pseudo-projective parsing is independent of parsing strategy but sensitive to language or treebank specific properties. By contrast, the construction specific transformations appear to be more sensitive to parsing strategy but have a constant positive effect over several languages.

  • 16.
    Nilsson, Jens
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nivre, Joakim
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Graph Transformations in Data-Driven Dependency Parsing2006In: Proceedings of the 44rd Annual Meeting of the Association for Computational Linguistics and 21th International Conference on Computational Linguistics (COLING-ACL 2006), July 17-21, 2006, Sydney, Australia, Association for Computational Linguistics, Stroudsburg , 2006, p. 257-264Conference paper (Refereed)
    Abstract [en]

    Transforming syntactic representations in order to improve parsing accuracy has been exploited successfully in statistical parsing systems using constituency-based representations. In this paper, we show that similar transformations can give substantial improvements also in data-driven dependency parsing. Experiments on the Prague Dependency Treebank show that systematic transformations of coordinate structures and verb groups result in a 10% error reduction for a deterministic data-driven dependency parser. Combining these transformations with previously proposed techniques for recovering nonprojective dependencies leads to state-of-the-art accuracy for the given data set.

  • 17.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Kübler, Sandra
    McDonald, Ryan
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Riedel, Sebastian
    Yuret, Deniz
    The CoNLL 2007 Shared Task on Dependency Parsing2007In: Proceedings of the CoNLL Shared Task Session of EMNLP-CoNLL 2007, Association for Computational Linguistics , 2007, p. 915–932-Conference paper (Other academic)
    Abstract [en]

    The Conference on Computational Natural Language Learning features a shared task, in which participants train and test their learning systems on the same data sets. In 2007, as in 2006, the shared task has been devoted to dependency parsing, this year with both a multilingual track and a domain adaptation track. In this paper, we define the tasks of the different tracks and describe how the data sets were created from existing treebanks for ten languages. In addition, we characterize the different approaches of the participating systems, report the test results, and provide a first analysis of these results.

  • 18.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    MaltParser: A Data-Driven Parser-Generator for Dependency Parsing2006In: Proceedings of the fifth international conference on Language Resources and Evaluation (LREC2006), May 24-26, 2006, Genoa, Italy, European Language Resource Association, Paris , 2006, p. 2216-2219Conference paper (Refereed)
    Abstract [en]

    We introduce MaltParser, a data-driven parser generator for dependency parsing. Given a treebank in dependency format, MaltParser can be used to induce a parser for the language of the treebank. MaltParser supports several parsing algorithms and learning algorithms, and allows user-defined feature models, consisting of arbitrary combinations of lexical features, part-of-speech features and dependency features. MaltParser is freely available for research and educational purposes and has been evaluated empirically on Swedish, English, Czech, Danish and Bulgarian.

  • 19. Nivre, Joakim
    et al.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nilsson, Jens
    Memory-Based Dependency ParsingManuscript (preprint) (Other (popular science, discussion, etc.))
  • 20.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Memory-Based Dependency Parsing.2004In: Proceedings of the Eighth Conference on Computational Natural Language Learning (CoNLL), Association for Computational Linguistics (ACL), Stroudsburg , 2004, p. 49-56Conference paper (Refereed)
    Abstract [en]

    This paper reports the results of experiments using memory-based learning

    to guide a deterministic dependency parser for unrestricted natural

    language text. Using data from a small treebank of Swedish,

    memory-based classifiers for predicting the next action of

    the parser are constructed. The accuracy of a classifier as

    such is evaluated on held-out data derived from the treebank,

    and its performance as a parser guide is evaluated by parsing

    the held-out portion of the treebank. The evaluation shows

    that memory-based learning gives a significant improvement

    over a previous probabilistic model based on maximum conditional

    likelihood estimation and that the inclusion of lexical features

    improves the accuracy even further.

  • 21.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datavetenskap.
    Chanev, Atanas
    Eryigit, Gülsen
    Kübler, Sandra
    Marinov, Svetoslav
    Marsi, Erwin
    MaltParser: A Language-Independent System for Data-Driven Dependency Parsing2007In: Natural Language Engineering, Vol. 13, no 2, p. 95-135Article in journal (Refereed)
    Abstract [en]

    Parsing unrestricted text is useful for many language technology applications but requires parsing methods that are both robust and efficient. MaltParser is a language-independent system for data-driven dependency parsing that can be used to induce a parser for a new language from a treebank sample in a simple yet flexible manner. Experimental evaluation confirms thatMaltParser can achieve robust, efficient and accurate parsing for a wide range of languages without language-specific enhancements and with rather limited amounts of training data.

  • 22.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Eryigit, Gülsen
    Department of Computer Engineering Istanbul Technical University.
    Marinov, Svetoslav
    School of Humanities and Informatics, University of Skövde.
    Labeled Pseudo-Projective Dependency Parsing with Support Vector Machines2006In: Labeled Pseudo-Projective Dependency Parsing with Support Vector Machines. In Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X)., June 8-9, 2006, New York City, Association for Computational Linguistics, Stroudsburg , 2006Conference paper (Refereed)
    Abstract [en]

    We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.

  • 23.
    Nivre, Joakim
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Nilsson, Jens
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Hall, Johan
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi.
    Talbanken05: A Swedish Treebank with Phrase Structure and Dependency Annotation2006In: Proceedings of the fifth international conference on Language Resources and Evaluation (LREC2006), May 24-26, 2006, Genoa, Italy, European Language Resource Association, Paris , 2006, p. 1392-1395Conference paper (Refereed)
    Abstract [en]

    We introduce Talbanken05, a Swedish treebank based on a syntactically annotated corpus from the 1970s, Talbanken76, converted to modern formats. The treebank is available in three different formats, besides the original one: two versions of phrase structure annotation and one dependency-based annotation, all of which are encoded in XML. In this paper, we describe the conversion process and exemplify the available formats. The treebank is freely available for research and educational purposes.

1 - 23 of 23
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf