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  • Articles  (12)
  • word sense disambiguation  (12)
  • Springer  (12)
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  • Articles  (12)
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  • Springer  (12)
  • American Meteorological Society
  • American Physical Society (APS)
  • De Gruyter
  • International Union of Crystallography
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  • 2000-2004  (12)
  • 1995-1999
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  • 2000  (12)
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  • 1
    Electronic Resource
    Electronic Resource
    Peeling an Onion: The Lexicographer's Experience ofManual Sense-Tagging (2000)
    Springer
    Computers and the humanities 34 (2000), S. 85-97 
    Details
    ISSN: 1572-8412
    Keywords: context/kwd〉 ; corpus ; evaluation ; lexicography ; part-of-speech tagging ; word sense disambiguation ; sense-tagging
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract SENSEVAL set itself the task of evaluating automaticword sense disambiguation programs (see Kilgarriff andRosenzweig, this volume, for an overview of theframework and results). In order to do this, it wasnecessary to provide a `gold standard' dataset of `correct' answers. This paper will describe thelexicographic part of the process involved in creatingthat dataset. The primary objective was for a group oflexicographers to manually examine keywords in a largenumber of corpus contexts, and assign to each contexta sense-tag for the keyword, taken from the Hectordictionary. Corpus contexts also had to be manuallypart-of-speech (POS) tagged. Various observationsmade and insights gained by the lexicographers duringthis process will be presented, including a critiqueof the resources and the methodology.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002407003264
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  • 2
    Electronic Resource
    Electronic Resource
    ROMANSEVAL: Results for Italian by SENSE (2000)
    Springer
    Computers and the humanities 34 (2000), S. 199-204 
    Details
    ISSN: 1572-8412
    Keywords: analogy-based NLP ; semantic similarity ; word sense disambiguation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract The paper describes SENSE, a word sense disambiguation system thatmakes use of different types of cues to infer the most likelysense of a word given its context. Architecture and functioning ofthe system are briefly illustrated. Results are given for theROMANSEVAL Italian test corpus of verbs.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002454919194
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  • 3
    Electronic Resource
    Electronic Resource
    Word Sense Disambiguation by Information Filtering and Extraction (2000)
    Springer
    Computers and the humanities 34 (2000), S. 127-134 
    Details
    ISSN: 1572-8412
    Keywords: word sense disambiguation ; information filtering ; SENSEVAL
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract We describe a simple approach to word sensedisambiguation using information filtering andextraction. The method fully exploits and extends theinformation available in the Hector dictionary. Thealgorithm proceeds by the application of severalfilters to prune the candidate set of word sensesreturning the most frequent if more than one remains.The experimental methodology and its implication arealso discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002423406899
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  • 4
    Electronic Resource
    Electronic Resource
    Simple Word Sense Discrimination (2000)
    Springer
    Computers and the humanities 34 (2000), S. 165-170 
    Details
    ISSN: 1572-8412
    Keywords: Senseval ; statistical WSD ; word sense disambiguation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract Wisdom is a system for performing word sense disambiguation (WSD)using a limited number of linguistic features and a simplesupervised learning algorithm. The most likely sense tag for aword is determined by calculating co-occurrence statistics forwords appearing within a small window. This paper gives abrief description of the components in the Wisdom system and thealgorithm used to predict the correct sense tag. Some results forWisdom from the Senseval competition are presented, and directionsfor future work are also explored.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002661023178
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  • 5
    Electronic Resource
    Electronic Resource
    Framework and Results for English SENSEVAL (2000)
    Springer
    Computers and the humanities 34 (2000), S. 15-48 
    Details
    ISSN: 1572-8412
    Keywords: evaluation ; SENSEVAL ; word sense disambiguation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract Senseval was the first open, community-based evaluation exercisefor Word Sense Disambiguation programs. It adopted the quantitativeapproach to evaluation developed in MUC and other ARPA evaluationexercises. It took place in 1998. In this paper we describe thestructure, organisation and results of the SENSEVAL exercise forEnglish. We present and defend various design choices for theexercise, describe the data and gold-standard preparation, considerissues of scoring strategies and baselines, and present the resultsfor the 18 participating systems. The exercise identifies thestate-of-the-art for fine-grained word sense disambiguation, wheretraining data is available, as 74–78% correct, with a number ofalgorithms approaching this level of performance. For systems thatdid not assume the availability of training data, performance wasmarkedly lower and also more variable. Human inter-tagger agreementwas high, with the gold standard taggings being around 95%replicable.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002693207386
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  • 6
    Electronic Resource
    Electronic Resource
    Word Sense Disambiguation Using the Classification Information Model (2000)
    Springer
    Computers and the humanities 34 (2000), S. 141-146 
    Details
    ISSN: 1572-8412
    Keywords: Classification Information Model ; classification information ; word sense disambiguation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract A Classification Information Model is a pattern classification model.The model decides the proper class of an input instance by integrating individual decisions, each of which is made with each feature in the pattern.Each individual decision is weighted according to the distributional property of the feature deriving the decision. An individual decision and its weight are represented as classification information which is extracted from the training instances.In the word sense disambiguation based on the model, the proper sense of an input instance is determined by the weighted sum of whole individual decisions derived from the features contained in the instance.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002450818285
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  • 7
    Electronic Resource
    Electronic Resource
    Using Semantic Classification Trees for WSD (2000)
    Springer
    Computers and the humanities 34 (2000), S. 187-192 
    Details
    ISSN: 1572-8412
    Keywords: semantic classification trees ; SENSEVAL ; word sense disambiguation ; WSD evaluation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract This paper describes the evaluation of a WSD method withinSENSEVAL. This method is based on Semantic Classification Trees (SCTs)and short context dependencies between nouns and verbs. The trainingprocedure creates a binary tree for each word to be disambiguated. SCTsare easy to implement and yield some promising results. The integrationof linguistic knowledge could lead to substantial improvement.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002467221920
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  • 8
    Electronic Resource
    Electronic Resource
    Senseval/Romanseval: The Framework for Italian (2000)
    Springer
    Computers and the humanities 34 (2000), S. 61-78 
    Details
    ISSN: 1572-8412
    Keywords: semantic tagging ; word sense disambiguation ; WSDS evaluation ; inter-annotator agreement ; Italian corpus annotation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract In this paper we present some observations concerning an experiment of (manual/automatic) semantic tagging of a small Italian corpus performed within the framework of the SENSEVAL/ROMANSEVAL initiative. Themain goal of the initiative was to set up a framework for evaluation of Word Sense Disambiguation systems (WSDS) through the comparative analysis of their performance on the same type of data. In this experiment there are two aspects which are of relevance: first, the preparation of the reference annotated corpus, and, second, the evaluation of the systems against it. In both aspects we are mainly interested here in the analysis of the linguistic side which can lead to a better understanding of the problem of semantic annotation of a corpus, be itmanual or automatic annotation. In particular, we will investigate, firstly, the reasons for disagreement between human annotators, secondly, some linguistically relevant aspects of the performance of the Italian WSDS and, finally, the lessons learned from the present experiment.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002419305990
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  • 9
    Electronic Resource
    Electronic Resource
    Hierarchical Decision Lists for Word Sense Disambiguation (2000)
    Springer
    Computers and the humanities 34 (2000), S. 179-186 
    Details
    ISSN: 1572-8412
    Keywords: word sense disambiguation ; decision lists ; supervised machine learning ; lexical ambiguity resolution ; SENSEVAL
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract This paper describes a supervised algorithm for word sensedisambiguation based on hierarchies of decision lists. This algorithmsupports a useful degree of conditional branching while minimizing thetraining data fragmentation typical of decision trees. Classificationsare based on a rich set of collocational, morphological and syntacticcontextual features, extracted automatically from training data andweighted sensitive to the nature of the feature and feature class. Thealgorithm is evaluated comprehensively in the SENSEVAL framework,achieving the top performance of all participating supervised systems onthe 36 test words where training data is available.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002674829964
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  • 10
    Electronic Resource
    Electronic Resource
    Introduction to the Special Issue on SENSEVAL (2000)
    Springer
    Computers and the humanities 34 (2000), S. 1-13 
    Details
    ISSN: 1572-8412
    Keywords: word sense disambiguation ; evaluation ; SENSEVAL
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Notes: Abstract Senseval was the first open, community-based evaluation exercise for WordSense Disambiguation programs. It took place in the summer of 1998,with tasks for English, French and Italian. There were participating systems from 23 researchgroups. This special issueis an account of the exercise. In addition to describing the contentsof the volume, this introduction considers how the exercise has shedlight on some general questions about wordsenses and evaluation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002619001915
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