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| Excerpt |
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Creates a bag of words / tfidf tag with the vector information for the document/text_block/sentence. Accumulates the vector until the engine cannot read any further |
Operates On: all lexical Items.
Saga_is_recognizer Recognizer false
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Configuration Parameters
Parameter summary JSON map resource in which the vocabulary is stored name vocabulary required true Parameter summary Type of algorithm to use then building the vector, can be either BOW or TF_IDF default BOW name vectorType required true Parameter summary Dataset ID from which the vocabulary was extracted name datasetId required true Parameter summary Minimum number of tokens to match default 1 name min type integer required true Parameter summary Maximum number of tokens to match default 2 name max type integer required true
| Saga_config_stage |
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"vocabulary": "saga-provider:saga_vocabulary", "vectorType": "BOW", "datasetId": "dataset-234ifgbqafgoail3", "min": 1, "max": 3, |
Example Output
In this example the stage load a predefined vocabulary to generate a vector for the sentence using BOW, the same is done but using TF_IDF
| Saga_graph |
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V---------------------------[The pilot landed safely the aircraft after gear failed when approaching the runaway.]----------------------------V
^-[The]-V-[pilot]-V-[landed]-V-[safely]-V-[the]-V-[aircraft]-V-[after]-V-[gear]-V-[failed]-V-[when]-V-[approaching]-V-[the]-V---[runaway.]----^
^-[the]-^ ^---[landed safely]---^---[the aircraft]---^---[after gear]---^---[failed when]---^---[approaching the]---^-[runaway]-V-[.]-^
^---[pilot landed]---^---[safely the]---^---[aircraft after]---^---[gear failed]---^---[when approaching]---^ ^---[runaway .]---^
^---[The pilot]---^ ^-----[the runaway.]------^
^---[the pilot]---^ ^---[the runaway]---^
^-------------------------------------------------------------------[{BOW}]-------------------------------------------------------------------^
V---------------------------[The pilot landed safely the aircraft after gear failed when approaching the runaway.]----------------------------V
^-[The]-V-[pilot]-V-[landed]-V-[safely]-V-[the]-V-[aircraft]-V-[after]-V-[gear]-V-[failed]-V-[when]-V-[approaching]-V-[the]-V---[runaway.]----^
^-[the]-^ ^---[landed safely]---^---[the aircraft]---^---[after gear]---^---[failed when]---^---[approaching the]---^-[runaway]-V-[.]-^
^---[pilot landed]---^---[safely the]---^---[aircraft after]---^---[gear failed]---^---[when approaching]---^ ^---[runaway .]---^
^---[The pilot]---^ ^-----[the runaway.]------^
^---[the pilot]---^ ^---[the runaway]---^
^-----------------------------------------------------------------[{TF_IDF}]------------------------------------------------------------------^ |
Output Flags
Lex-Item Flags:
- WEIGHT_VECTOR - Identifies the tag as a weight vector representation of a sentence
- TOKEN - Identifies that the Lex-Items produced by this stage are tokens and not text blocks.
Vertex Flags:
| Info |
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No vertices are created in this stage |
Resource Data
Description of resource.
Resource Format
| Saga_json | ||
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"count" : 15, "docsPerTerm" : 15, "datasetId" : "f92e1394-5f52-3331-aa6a-9c510ad31da5", "tokenCount" : 1, "docCount" : 204021, "word" : "depict" |
Fields
Parameter summary number of time the word appeared name count type integer required true Parameter summary Number of document in which the word appeared name docsPerTerm type integer required true Parameter summary dataset ID in from which the vocabulary was extracted name datasetId required true Parameter summary number of tokens for the word name tokenCount type integer required true Parameter summary number of documents in the dataset name docCount type integer required true Parameter summary word of the vocabulary name word required true
Overview
Content Tools