Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse syntaxique par constituants× | Analyse des dépendances syntaxiques× | |
|---|---|---|
| Domaine | Fouille de textes | Fouille de textes |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2003 | — |
| Auteur d'origine≠ | Michael Collins (statistical models, 2003) | — |
| Type | NLP syntactic-analysis task | NLP syntactic-analysis task |
| Source fondatrice≠ | Collins, M. (2003). Head-Driven Statistical Models for Natural Language Parsing. Computational Linguistics, 29(4), 589-637. DOI ↗ | Nivre, J. (2005). Dependency Grammar and Dependency Parsing. MSI Report. link ↗ |
| Alias | phrase-structure parsing, constituent parsing, Kurucu Öbek Ayrıştırma (Constituency Parsing) | syntactic dependency analysis, dependency tree parsing, Bağımlılık Ayrıştırma (Dependency Parsing) |
| Apparentées | 3 | 3 |
| Résumé≠ | Constituency parsing is a natural-language-processing task that represents a sentence as a tree of recursively nested phrase-structure constituents — for example S → NP + VP. Building on the head-driven statistical parsing models introduced by Collins (2003) and the later neural parsers of Kitaev and colleagues (2019), it exposes the hierarchical syntactic skeleton of a sentence for grammatical pattern extraction and grammar research. | 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. |
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