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RNN-for-Joint-NLU

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/pdf/1609.01454.pdf)

Intent prediction and slot filling are performed in two branches based on Encoder-Decoder model.

dataset (Atis)

You can get data from here

Requirements

  • Pytorch 0.2

Train

python3 train.py --data_path 'your data path e.g. ./data/atis-2.train.w-intent.iob'

Result


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jupyter-notebook (5,865
lstm (265
rnn (165
attention (105
nlu (55
encoder-decoder (39
intent (25
slot-filling (14

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