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| Chunking× | Part-of-Speech-Tagging (POS-Tagging)× | |
|---|---|---|
| Fachgebiet | Text Mining | Text Mining |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1991 | — |
| Urheber≠ | Steven Abney | — |
| Typ≠ | NLP partial-parsing task | NLP sequence-labelling task |
| Wegweisende Quelle≠ | Abney, S. (1991). Parsing by Chunks. In Principle-Based Parsing. Kluwer Academic Publishers. ISBN: 978-0-7923-1173-4 | Ratnaparkhi, A. (1996). A Maximum Entropy Model for Part-Of-Speech Tagging. EMNLP. link ↗ |
| Aliasnamen | shallow parsing, partial parsing, Yüzeysel Ayrıştırma (Chunking) | part-of-speech tagging, grammatical tagging, Sözcük Türü Etiketleme (POS Tagging) |
| Verwandt≠ | 4 | 3 |
| Zusammenfassung≠ | Chunking, also called shallow parsing, is a natural-language-processing task introduced by Steven Abney in 1991 that divides text into grammatical pieces — such as noun phrases and verb phrases — using part-of-speech tags. It extracts useful syntactic structure quickly without building a full parse tree of the sentence. | Part-of-speech tagging assigns a grammatical category label — noun, verb, adjective, and so on — to every word in a text. It is a foundational natural-language-processing task, formalised as a statistical model by Ratnaparkhi (1996) and packaged into widely used toolkits such as Stanford CoreNLP (Manning et al., 2014), and it serves as a preliminary step for syntactic analysis and information extraction. |
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