Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/lrec2008/papers/144> ?p ?o. }
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- 144 creator cedric-messiant.
- 144 creator thierry-poibeau.
- 144 type InProceedings.
- 144 label "Do we Still Need Gold Standards for Evaluation?".
- 144 sameAs 144.
- 144 abstract "The availability of a huge mass of textual data in electronic format has increased the need for fast and accurate techniques for textual data processing. Machine learning and statistical approaches have been increasingly used in NLP since a decade, mainly because they are quick, versatile and efficient. However, despite this evolution of the field, evaluation still rely (most of the time) on a comparison between the output of a probabilistic or statistical system on the one hand, and a non-statistic, most of the time hand-crafted, gold standard on the other hand. In this paper, we take the example of the acquisition of subcategorization frames from corpora as a practical example. Our study is motivated by the fact that, even if a gold standard is an invaluable resource for evaluation, a gold standard is always partial and does not really show how accurate and useful results are.".
- 144 hasAuthorList authorList.
- 144 hasTopic Linguistics.
- 144 isPartOf proceedings.
- 144 keyword "Evaluation methodologies".
- 144 keyword "Tools, systems, applications".
- 144 keyword "Validation of LRs".
- 144 title "Do we Still Need Gold Standards for Evaluation?".