The ATIS (Airline Travel Information Systems) is a dataset consisting of audio recordings and corresponding manual transcripts about humans asking for flight information on automated airline travel inquiry systems. The data consists of 17 unique intent categories. The original split contains 4478, 500 and 893 intent-labeled reference utterances in train, development and test set respectively.
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The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity:
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Dataset composed of online banking queries annotated with their corresponding intents.
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This project contains natural language data for human-robot interaction in home domain which we collected and annotated for evaluating NLU Services/platforms.
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Dataset is constructed from single intent dataset ATIS.
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HINT3 is a dataset for intent detection. It consists of 3 different datasets each containing a diverse set of intents in a single domain - mattress products retail, fitness supplements retail and online gaming named SOFMattress, Curekart and Powerplay11.
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The Multimodal Document Intent Dataset (MDID) is a dataset for computing author intent from multimodal data from Instagram. It contains 1,299 Instagram posts covering a variety of topics, annotated with labels from three taxonomies. The samples are labelled with 7 labels of intent: Provocative, Informative, Advocative, Entertainment, Expositive, Expressive, Promotive
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