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- 631 creator zdravko-dovedan.
- 631 type InProceedings.
- 631 label "Rule-Based Chunker for Croatian".
- 631 sameAs 631.
- 631 abstract "In this paper we discuss a rule-based approach to chunking sentences in Croatian, implemented using local regular grammars within the NooJ development environment. We describe the rules and their implementation by regular grammars and at the same time show that in NooJ environment it is extremely easy to fine tune their different sub-rules. Since Croatian has strong morphosyntactic features that are shared between most or all elements of a chunk, the rules are built by taking these features into account and strongly relying on them. For the evaluation of our chunker we used a extracted set of manually annotated sentences from 100 kw MSD/tagged and disambiguated Croatian corpus. Our chunker performed the best on VP-chunks (F: 97.01), while NP-chunks (F: 92.31) and PP-chunks (F: 83.08) were of lower quality. The results are comparable to chunker performance of CoNLL-2000 shared task of chunking.".
- 631 hasAuthorList authorList.
- 631 hasTopic Linguistics.
- 631 isPartOf proceedings.
- 631 keyword "Grammars".
- 631 keyword "MultiWord Expressions & Collocations".
- 631 keyword "Parsing Systems".
- 631 title "Rule-Based Chunker for Croatian".
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- item-1 hasContent kristina-vuckovic.
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- item-2 hasContent marko-tadic.
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- item-3 hasContent zdravko-dovedan.
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- 632 creator djamel-mostefa.
- 632 creator khalid-choukri.
- 632 creator nicolas-moreau.
- 632 creator rainer-stiefelhagen.
- 632 creator susanne-burger.
- 632 type InProceedings.
- 632 label "Data Collection for the CHIL CLEAR 2007 Evaluation Campaign".
- 632 sameAs 632.
- 632 abstract "This paper describes in detail the data that was collected and annotated during the third and final year of the CHIL project. This data was used for the CLEAR evaluation campaign in spring 2007. The paper also introduces the CHIL Evaluation Package 2007 that resulted from this campaign including a complete description of the performed evaluation tasks. This evaluation package will be made available to the community through the ELRA General Catalogue.".
- 632 hasAuthorList authorList.
- 632 hasTopic Linguistics.
- 632 isPartOf proceedings.
- 632 keyword "Corpus (creation, annotation, etc.)".
- 632 keyword "LR national/international projects, organizational/policy issues".
- 632 keyword "Multimedia annotation and processing".
- 632 title "Data Collection for the CHIL CLEAR 2007 Evaluation Campaign".
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- item-1 hasContent nicolas-moreau.
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- item-2 hasContent djamel-mostefa.
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- item-3 hasContent rainer-stiefelhagen.
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- item-4 hasContent susanne-burger.
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- item-5 hasContent khalid-choukri.
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- 635 creator stephan-busemann.
- 635 creator yajing-zhang.
- 635 type InProceedings.
- 635 label "Identifying Foreign Person Names in Chinese Text".
- 635 sameAs 635.
- 635 abstract "Foreign name expressions written in Chinese characters are difficult to recognize since the sequence of characters represents the Chinese pronunciation of the name. This paper suggests that known English or German person names can reliably be identified on the basis of the similarity between the Chinese and the foreign pronunciation. In addition to locating a person name in the text and learning that it is foreign, the corresponding foreign name is identified, thus gaining precious additional information for cross-lingual applications. This idea is implemented as a statistical module into the rule-based shallow parsing system SProUT, forming the HyFex system. The statistical component is invoked if a sequence of trigger characters is found that may correspond to a foreign name. Their phonetic Pinyin representation is produced and compared to the phonetic representations (SAMPA) of given foreign names, which are generated by the MARY TTS system for German and English pronunciations. This comparison is achieved by a hand-crafted metric that assigns costs to specific edit operations. The person name corresponding to the SAMPA representation with the lowest costs attached is returned as the most similar result, if a threshold is not exceeded. Our evaluation on publicly available data shows competitive results.".
- 635 hasAuthorList authorList.
- 635 hasTopic Linguistics.
- 635 isPartOf proceedings.
- 635 keyword "Named Entity recognition".
- 635 keyword "Statistical methods".
- 635 keyword "Tools, systems, applications".
- 635 title "Identifying Foreign Person Names in Chinese Text".
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- item-1 hasContent stephan-busemann.
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- item-2 hasContent yajing-zhang.
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- 638 creator eva-hajicova.
- 638 creator lucie-mladova.
- 638 creator sarka-zikanova.
- 638 type InProceedings.
- 638 label "From Sentence to Discourse: Building an Annotation Scheme for Discourse Based on Prague Dependency Treebank".
- 638 sameAs 638.