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ملء الخانات×استخلاص المعلومات×
المجالتنقيب النصوصتنقيب النصوص
العائلةProcess / pipelineProcess / pipeline
سنة النشأة2018 (joint slot-gate model); BIO tagging foundations earlier
صاحب الطريقةEstablished via NER/IOB tagging literature; popularised for dialogue by Goo et al. (2018) and Chen et al. (2019)
النوعNLP token-classification / information-extraction taskNLP structured-information task
المصدر التأسيسيGoo, C.W., Gao, G., Hsu, Y.K., Huo, C.L., Chen, T.C., Hsu, S.C., & Chen, Y.N. (2018). Slot-Gated Modeling for Joint Slot Filling and Intent Prediction. Proceedings of NAACL-HLT 2018. link ↗Cowie, J. & Lehnert, W. (1996). Information Extraction. Communications of the ACM. DOI ↗
الأسماء البديلةslot doldurma, Slot Doldurma (Slot Filling / NER-NLU), information slot extraction, dialogue slot fillingIE, structured information extraction, Bilgi Çıkarma (Information Extraction)
ذات صلة54
الملخصSlot filling is a natural-language-understanding task that extracts predefined template fields — such as date, location, or product name — from a user utterance. It emerged as a core component of dialogue systems and form-based information extraction, and became widely studied after Goo et al. (2018) introduced the Slot-Gated Model for joint slot filling and intent prediction, followed by Chen et al. (2019) who extended the paradigm with BERT-based joint modelling.Information extraction (IE) is a natural-language-processing task that converts unstructured text into structured information — such as events, relations, and attributes — so that facts buried in free-form documents become machine-readable records. The task was consolidated in early surveys by Cowie and Lehnert (1996) and later by Grishman (2012).
ScholarGateمجموعة البيانات
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ScholarGateقارن الطرق: Slot Filling · Information Extraction. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare