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| Anàlisi de dependències× | Reconeixement d'Entitats Nomenades (NER)× | |
|---|---|---|
| Camp | Mineria de text | Mineria de text |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen | — | — |
| Autor original | — | — |
| Tipus≠ | NLP syntactic-analysis task | NLP sequence-labelling task |
| Font seminal≠ | Nivre, J. (2005). Dependency Grammar and Dependency Parsing. MSI Report. link ↗ | Nadeau, D. & Sekine, S. (2007). A survey of named entity recognition. Lingvisticae Investigationes. link ↗ |
| Àlies | syntactic dependency analysis, dependency tree parsing, Bağımlılık Ayrıştırma (Dependency Parsing) | NER, entity tagging, Adlandırılmış Varlık Tanıma (NER) |
| Relacionats | 3 | 3 |
| Resum≠ | Dependency parsing is a natural-language-processing task that reveals the syntactic dependency relations between the words of a sentence as a tree structure. Surveyed in the dependency-grammar tradition by Nivre (2005) and made fast and accurate with neural networks by Chen and Manning (2014), it is commonly used as a prerequisite step for information extraction and relation detection. | Named entity recognition (NER) is a natural-language-processing task that automatically detects and labels entities in text — such as people, organisations, locations, and dates. Surveyed by Nadeau and Sekine (2007) and later advanced with neural architectures by Lample et al. (2016), it turns free-running text into tagged spans that downstream tools can use. |
| ScholarGateConjunt de dades ↗ |
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