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Creates n-grams from TOKEN lex items of size min-max. Breaks n-grams on SPLIT_FLAGS |
Operates On: Lexical Items with TOKEN and possibly other flags as specified below.
Saga_is_recognizer Recognizer false
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"min": 2, "max": 3, "splitFlags": [], "ignoreOnBoundaryFlags": [] |
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V--------------[abraham lincoln likes macaroni and cheese]--------------------VV ^--[abraham]--V--[lincoln]--V--[likes]--V--[macaroni]--V--[and]--V--[cheese]--^ ^---[abraham lincoln]---^---[likes macaroni]---^---{place}[and cheese]---^ ^----{food}-[lincoln likes]---^---[macaroni and]---^ ^---{food}---^ ^[abraham lincoln likes]-----^------{person}----[macaroni and cheese]-----^ ^-----[likes macaroni and]-----^ ^-------{food}----[lincoln likes macaroni]----------^ |
Info |
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No vertices are created in this stage |
Description of resource.
Saga_json | ||
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"_id" : "KGAAJGsBemSwA0nZTLXA",
"tag": "recipe",
"pattern": "("how many"|"how much") {ingredient} ",
"confAdjust": 0.95
. . . additional fields as needed go here . . . |
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These will all be added to the interpretation graph with the SEMANTIC_TAG flag.
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Tags are hierarchical representations of the same intent. For example, {city} → {administrative-area} → {geographical-area} |
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