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Synther -- A New M-Gram Pos Tagger (2003)
| Content Provider | CiteSeerX |
|---|---|
| Author | Undermann, David Sündermann, David Ney, Hermann |
| Description | In this paper, the Part-Of-Speech (POS) tagger synther based on m-gram statistics is described. After explaining its basic architecture, three smoothing approaches and the strategy for handling unknown words is exposed. Subsequently, synther's performance is evaluated in comparison with four state-of-the-art POS taggers. All of them are trained and tested on three corpora of di#erent languages and domains. In the course of this evaluation, synther resulted in the lowest error rates or at least below average error rates. Finally, it is shown that the linear interpolation smoothing strategy with coverage-dependent weights features better properties than the two other approaches. |
| File Format | |
| Language | English |
| Publisher Date | 2003-01-01 |
| Publisher Institution | In Proc. NLP-KE, 628–633, Bejing |
| Access Restriction | Open |
| Subject Keyword | Unknown Word Linear Interpolation Tagger Synther Error Rate Di Erent Language Average Error Rate State-of-the-art Po Tagger M-gram Statistic New M-gram Po Tagger Basic Architecture Coverage-dependent Weight Feature |
| Content Type | Text |
| Resource Type | Article |
