Text Analytics APIs
The Text Analytics APIs directly separate the Intelligent Virtual Assistant (IVA) and Text Analyzer rules into independent modules. The introduction of modularity between these components provides more reliability by preventing potential IVA integration issues each time a text analyzer configuration changes.
APIs for text analyzers
The APIs cover all scenarios in which the IVA uses text analyzers, for example:
- Adding and removing models from text analyzers
- pxAddModelInTextAnalyzer
- pxRemoveModelFromTextAnalyzer
For more information, see Adding and removing models from text analyzers.
- Configuring text analyzers
- pxConfigureTextAnalyzer
For more information, see Configuring text analyzers.
- Performing the Save As operation in the text analyzer
- pxSaveAsTextAnalyzer
For more information, see Performing the Save As operation in text analyzer.
APIs for building text analytics models
The APIs handle such model-building activities as:
- Adding and deleting languages from models
- pxAddLanguageToModel
- pxDeleteLanguageFromModel
For more information, see Adding and deleting languages from models.
- Adding model feedback
- pxCaptureTAFeedback
- pxUpdateModels
- pxCopyNLPFeedback
For more information, see Adding model feedback.
- Creating new models
- pxCreateEmptyModel
- pxSaveAsModelAPI
For more information, see Creating new models.
- Returning model analysis and specifying the repository for model training
data
- D_pxGetModelAnalysis
- pxSetPredictionRepository
For more information, see Returning model analysis and specifying the repository for model training data.
APIs for listing models and entity types
Additionally, the APIs can provide lists of all available text analytics models and entity types, for example:
- D_pxTopicsInModel
- D_pxTopicsInTextAnalyzer
- D_pxListModelsInTextAnalyzerByType
- D_pzEntityTypesInTextAnalyzer
- D_pzGetEntityTypesForModel
For more information, see Listing all available text analytics models and entity types.
Previous topic Learning natural language processing with NLP Sample Next topic Adding and removing models from text analyzers