Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Dependency Parsing× | Kerneferentie-resolutie× | |
|---|---|---|
| Vakgebied | Tekstmining | Tekstmining |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | — | 1978 |
| Grondlegger≠ | — | Hobbs (1978); Lee et al. (2017, neural end-to-end) |
| Type≠ | NLP syntactic-analysis task | NLP information-extraction task |
| Oorspronkelijke bron≠ | Nivre, J. (2005). Dependency Grammar and Dependency Parsing. MSI Report. link ↗ | Lee, K. et al. (2017). End-to-end Neural Coreference Resolution. EMNLP. link ↗ |
| Aliassen | syntactic dependency analysis, dependency tree parsing, Bağımlılık Ayrıştırma (Dependency Parsing) | coreference, anaphora resolution, Eşgönderim Çözümleme (Coreference Resolution) |
| Verwant≠ | 3 | 4 |
| Samenvatting≠ | 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. | Coreference resolution is a natural-language-processing task that detects when different expressions in a text refer to the same entity — for example a name, a later pronoun, and a descriptive phrase all pointing at one person. Rooted in early linguistic work by Hobbs (1978) and advanced by the end-to-end neural model of Lee et al. (2017), it improves the quality of information extraction and text understanding. |
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