Systems and methods implementing data query language and utterance corpus implements for handling slot-filling and dialogue intent classification data in a machine learning task-oriented dialogue system

A method of implementing an intuitive search interface for tactically searching one or more annotated training corpora in a machine learning-based dialogue system, the method comprising:

• identifying a training corpus query for searching one or more annotated training corpora of a machine learning-based dialogue system, wherein each of the one or more annotated training corpora include a plurality of annotated training samples according to a prescribed annotation format;
• constructing one or more portions of the training corpus query into one or more search expressions based on the prescribed annotation format of the one or more annotated training corpora, wherein each of the one or more search expressions is recognizable to a training sample retrieval program that searchably interfaces with the one or more annotated training corpora of the machine learning-based dialogue system;
• retrieving a subset of annotated training samples from the plurality of annotated training samples based on satisfying the one or more search expressions associated with the training corpus query;
• and
• returning the subset of annotated training samples to an intuitive training corpus search interface based on the retrieval.

A method of implementing an intuitive search interface for tactically searching one or more annotated utterance corpora in a machine learning-based dialogue system, the method comprising:

• identifying an utterance corpus query for searching a plurality of annotated utterance samples of one or more annotated utterance corpora of a machine learning-based dialogue system, wherein each of the plurality of annotated utterance samples include a distinct utterance sample comprising a string of tokens and an annotation portion inline with the string of tokens of the distinct utterance sample;
• interpreting the utterance corpus query by translating the utterance corpus query into one or more search expressions recognizable to an utterance sample retrieval program searchably interfacing with the one or more annotated utterance corpora of the machine learning-based dialogue system;
• retrieving a subset of annotated utterance samples from the one or more annotated utterance corpora based on the interpretation of the utterance corpus query;
• and
• returning the subset of annotated utterance samples to an intuitive utterance corpus search interface.