natural-language-processing
Slot Filling
3260 papers • 126 benchmarks • 313 datasets
The goal of Slot Filling is to identify from a running dialog different slots, which correspond to different parameters of the user’s query. For instance, when a user queries for nearby restaurants, key slots for location and preferred food are required for a dialog system to retrieve the appropriate information. Thus, the main challenge in the slot-filling task is to extract the target entity. Source: Real-time On-Demand Crowd-powered Entity Extraction Image credit: Robust Retrieval Augmented Generation for Zero-shot Slot Filling
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in slot-filling
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ATIS
ATIS
SLURP
SLURP
KILT: T-REx
KILT: T-REx
Libraries
iUse these libraries to find slot-filling models and implementations
3 papers 77
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Most implemented papers
BERT for Joint Intent Classification and Slot Filling
Qian Chen, Zhu Zhuo, Wen Wang•Wed Feb 27 2019
This work proposes a joint intent classification and slot filling model based on BERT that achieves significant improvement on intent classification accuracy, slot filling F1, and sentence-level semantic frame accuracy on several public benchmark datasets, compared to the attention-based recurrent neural network models and slot-gated models.
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