7.00.02 - NER Functions (Maximum Entropy Model Implementation) - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
Release Date
September 2017
Content Type
Programming Reference
User Guide
Publication ID
English (United States)

The NER functions that use the maximum entropy model are:

  • TrainNamedEntityFinder, which takes training data and outputs a maximum entropy model
  • FindNamedEntity, which takes input documents and extracts specified entities, using a maximum entropy model and, if appropriate, rules (regular expressions) or a dictionary

    The function uses a model to extract the entity types "person", "location", and "organization" and rules to extract the entity types "date", "time", "email" and "money". If you specify these entity names, the function invokes the default model types and model file names. To extract all entities in one FindNamedEntity call, specify "all".

  • Evaluate Named Entity Finder, which evaluates a maximum entropy model model

The maximum entropy model implementation supports only English text. The CRF model implementation supports English, simplified Chinese, and traditional Chinese text.

The NER functions that use the Conditional Random Fields (CRF) Model are documented in NER Functions (CRF Model Implementation).