FIAD is a new resource that encodes three Korean utterance patterns from banking reviews into Local Grammar Graphs to generate diverse annotated NLU training data, producing strong intent and topic extraction results on DIET-based models.
ArXiv, abs/2004.09936
2 Pith papers cite this work, alongside 113 external citations. Polarity classification is still indexing.
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Local grammar graphs generate 700 million labelled utterances that train a DIET classifier to 91% F1 for a Korean legal chatbot answering queries with links to public case documents.
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Building Korean linguistic resource for NLU data generation of banking app CS dialog system
FIAD is a new resource that encodes three Korean utterance patterns from banking reviews into Local Grammar Graphs to generate diverse annotated NLU training data, producing strong intent and topic extraction results on DIET-based models.
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Generating training datasets for legal chatbots in Korean
Local grammar graphs generate 700 million labelled utterances that train a DIET classifier to 91% F1 for a Korean legal chatbot answering queries with links to public case documents.