Sentence Classifier Stage

The sentence classifier stage uses OpenNLP's DocumentCategorizer to load classification models and tag sentences that match the binary classification model (is or isn't of a certain category) given a certain threshold of accuracy.

Operates On: Lexical Items within TEXT_BLOCK_SPLIT or SENTENCE_SPLIT flags.

Library: saga-classification-trainer-stage

Models can be trained directly with OpenNLP tools or from the Saga UI. See Classifier Recognizer in the User Manual for more information on how to create a model using Saga.

The stage will use the boundaryFlags specified to split the input text in sentences. All text between boundaries will be considered a sentence and will be evaluated separately by the classifier.

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.

Example Configuration

{
 "type":"ClassificationStage",
 "tagWith": "NAME-OF-OUTPUT-TAG", 
 "prob": "0.95", 
 "model": ".\model-file.bin"
}

Example Output

For this case a sentence breaker stage was configured before the classifier stage. tagWith value is animal-incident for this example

 V-------------------------------------[BIRD STRIKE DURING DESCENT. DAMAGE LIMITED TO 18 INCH DENT BOTTOM OUTBOARD SIDE OF ENGINE COWLING.]--------------------------------------V 
 ^-----------[BIRD STRIKE DURING DESCENT]-----------V------------------------[DAMAGE LIMITED TO 18 INCH DENT BOTTOM OUTBOARD SIDE OF ENGINE COWLING]------------------------V-[]-^ 
 ^---[BIRD]---V---[STRIKE]---V-[DURING]-V-[DESCENT]-^--[DAMAGE]--V-[LIMITED]-V-[TO]-V-[18]-V-[INCH]-V-[DENT]-V-[BOTTOM]-V-[OUTBOARD]-V-[SIDE]-V-[OF]-V-[ENGINE]-V-[COWLING]-^      
 ^---[bird]---^---[strike]---^-[during]-^-[descent]-^--[damage]--^-[limited]-^-[to]-^      ^-[inch]-^-[dent]-^-[bottom]-^-[outboard]-^-[side]-^-[of]-^-[engine]-^-[cowling]-^      
 ^--[{bird}]--^-[{physical}]-^--[dure]--^           ^-[{damage}]-^--[limit]--^                                                                                                     
 ^-[{animal}]-^--[{damage}]--^                                                                                                                                                     
 ^---------------[{animal-incident}]----------------^

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Generic Configuration Parameters

Configuration Parameters

Output Flags

Lex-Item Flags:

Vertex Flags: