NLP- Specific Operators
A group of operators is specifically designed to be useful in NLP models. They are
- Calls diffuse operator.
- Adds property to node or changes property
- Allows alternatives to be specified for words or objects
- Maintains consistency in parse structure
- Requires two alternatives to be present for propagation
- Sequences the operations during parse structure building
- Checks by running along chain looking for things
- Allows for specification of collocations in various ways
- Inserts symbol into parse chain
- Introduces new property to an object based on its context
- Supports different meanings
- Connects to members of ObjectGroup
- Prevents finding particular parent
- Prunes inconsistent meanings
- Any symbol but this one.
- Requires other specific alternatives not to be present for propagation to occur
- A representation of a group of objects
- Gathering object properties while ignoring word properties
- Embedding an operator which tests the objects in an ObjectGroup
- Joins pairs of words in parse chain at foot of parse structure
- Using related objects to improve anaphoric discrimination
- Builds parse structure by cloning itself when a pattern match is detected
- Linking synonyms that require mapping of parameters, such as ToBuy and ToSell
- Checks real properties of objects in grammatical structure
Operators that form a class hierarchy
are also used extensively in NLP models.
Map Functions perform constraint
reasoning in maps.
See Operators in large parsing model