مقایسهٔ روش‌ها

	برچسب‌گذاری نقش معنایی (SRL)	شناسایی رویداد	بازشناسی موجودیت نام‌دار (NER)
حوزه	متن‌کاوی	متن‌کاوی	متن‌کاوی
خانواده	Process / pipeline	Process / pipeline	Process / pipeline
سال پیدایش	2002	—	—
پدیدآور	Daniel Gildea & Daniel Jurafsky	—	—
نوع	NLP shallow semantic parsing task	NLP information-extraction task	NLP sequence-labelling task
منبع بنیادین	Gildea, D. & Jurafsky, D. (2002). Automatic Labeling of Semantic Roles. Computational Linguistics, 28(3), 245-288.	Doddington, G. et al. (2004). The Automatic Content Extraction (ACE) Program — Tasks, Data, and Evaluation. LREC.	Nadeau, D. & Sekine, S. (2007). A survey of named entity recognition. Lingvisticae Investigationes.
نام‌های دیگر	SRL, shallow semantic parsing, Anlamsal Rol Etiketleme (SRL)	event extraction, Olay Tespiti (Event Detection)	NER, entity tagging, Adlandırılmış Varlık Tanıma (NER)
مرتبط	3	4	3
خلاصه	Semantic role labeling, introduced by Gildea and Jurafsky in 2002, is a natural-language-processing task that assigns semantic roles — who did what to whom, where, when, and how — to the components around a verb (predicate) in a sentence. It turns plain text into structured predicate-argument representations and is a foundational tool for event extraction.	Event detection is a natural-language-processing information-extraction task that finds events, historical developments, and action expressions in text and classifies them by type. It grew out of the Automatic Content Extraction (ACE) program described by Doddington et al. (2004) and is widely used in news analysis and historical research.	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.