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The name predictor stage uses OpenNLP's NameFinder to load Name Entity Recognizer models and tag tokens that match entities based on the model given a certain threshold of accuracy.
Operates On: Lexical Items with TOKEN within TEXT_BLOCK_SPLIT and SENTENCE_SPLIT vertex flags.
Library: saga-name-trainer-stage
Generic Configuration Parameters
-
boundaryFlags ( type=string array
| optional
)
- List of vertex flags that indicate the beginning and end of a text block.
Tokens to process must be inside two vertices marked with this flag (e.g ["TEXT_BLOCK_SPLIT"]) -
skipFlags ( type=string array
| optional
)
- Flags to be skipped by this stage.
Tokens marked with this flag will be ignored by this stage, and no processing will be performed. -
requiredFlags ( type=string array
| optional
)
- Lex items flags required by every token to be processed.
Tokens need to have all of the specified flags in order to be processed. -
atLeastOneFlag ( type=string array
| optional
)
- Lex items flags needed by every token to be processed.
Tokens will need at least one of the flags specified in this array. -
confidenceAdjustment ( type=double
| default=1
| required
)
- Adjustment factor to apply to the confidence value of 0.0 to 2.0 from (Applies for every pattern match).
- 0.0 to < 1.0 decreases confidence value
- 1.0 confidence value remains the same
- > 1.0 to 2.0 increases confidence value
-
debug ( type=boolean
| default=false
| optional
)
- Enable all debug log functionality for the stage, if any.
-
enable ( type=boolean
| default=true
| optional
)
- Indicates if the current stage should be consider for the Pipeline Manager
- Only applies for automatic pipeline building
Configuration Parameters
-
tagWith ( type=string
| default=match
| optional
)
- if used with automatic pipeline creation, it assigns the tag to which the recognizer belongs to.
-
prob ( type=double
| default=0.95
| optional
)
- Probability threshold. Will only tag sentences that match better or equal to prob.
-
model ( type=string
| optional
)
- File location of the model.
-
normalize ( type=string array
| optional
)
- List of Tags used to normalize the text
- For example, let's say you want to normalize all different numbers in the text. You can create a "Numeric" tag using the numeric recognizer, that way each different number will me normalized to "{Numeric}".
$action.getHelper().renderConfluenceMacro("$codeS$body$codeE")
Example Output
$action.getHelper().renderConfluenceMacro("$codeS$body$codeE")
Output Flags
Lex-Item Flags
- SEMANTIC_TAG - Identifies all lexical items that are semantic tags.
- ML_TOKEN - Placed on tokens that find a match of a named entity from the model.
Vertex Flags