পদ্ধতির তুলনা করুন

	উদ্দেশ্য শনাক্তকরণ	নামযুক্ত সত্তা শনাক্তকরণ (NER)
ক্ষেত্র	টেক্সট খনন	টেক্সট খনন
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	—	—
প্রবর্তক	—	—
ধরন	NLP / NLU text-classification task	NLP sequence-labelling task
মৌলিক উৎস	Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP.	Nadeau, D. & Sekine, S. (2007). A survey of named entity recognition. Lingvisticae Investigationes.
অপর নাম	intent classification, intent recognition, Niyet Tespiti (Intent Detection)	NER, entity tagging, Adlandırılmış Varlık Tanıma (NER)
সম্পর্কিত	4	3
সারসংক্ষেপ	Intent detection is a natural-language-understanding task that classifies the purpose behind a user utterance — such as making a reservation, asking for information, or filing a complaint — into one of a set of predefined intent classes. It is a core NLU component of conversational interfaces and customer-service automation systems, drawing on the benchmarks of Larson et al. (2019) and Casanueva et al. (2020).	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.