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| 의존 구문 분석× | 개체명 인식 (NER)× | |
|---|---|---|
| 분야 | 텍스트 마이닝 | 텍스트 마이닝 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도 | — | — |
| 창시자 | — | — |
| 유형≠ | NLP syntactic-analysis task | NLP sequence-labelling task |
| 원전≠ | 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 ↗ |
| 별칭 | syntactic dependency analysis, dependency tree parsing, Bağımlılık Ayrıştırma (Dependency Parsing) | NER, entity tagging, Adlandırılmış Varlık Tanıma (NER) |
| 관련 | 3 | 3 |
| 요약≠ | 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. |
| ScholarGate데이터셋 ↗ |
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