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This stage works in a similar way to the Dictionary Tagger stage in the sense that looks up sequences of tokens in a dictionary to match the text being processed. The difference is that it will also include in the matching text N tokens to the right and/or left of the original matched text. |
Operates On: Lexical Items with TOKEN and possibly other flags as specified below.
Saga_is_recognizer
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"dictionary": "dict-provider:token_matcher_patterns", "groupTokens": false, "leftGroupTagName": "_leftTokens_", "matchGroupTagName": "_matchedTokens_", "rightGroupTagName": "_rightTokens_", "boundaryFlags": ["TEXT_BLOCK_SPLIT"], "requiredFlags": [], "skipFlags": : [], "atLeastOneFlag": [], "confidenceAdjustment": 1, "debug": false, "enable": true |
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V-----------------[call 333-4444 for pizza]------------------V ^------[call]------V-----[333-4444]------V-[for]-V--[pizza]--^ ^-[{_leftTokens_}]-^---[{phonenumber}]---^-[{_rightTokens_}]-^ ^-[{_matchedTokens_}]-^ ^----------------------[{pizza_phone}]-----------------------^ |
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No vertices are created in this stage |
Token matcher must have a dictionary of patterns which is a list of JSON records.
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"_id" : "Nlp3kXYBOOvNPbzJXDcQ", "tag": "qVRZi3YBvyJs83wnkfik", "pattern": "{phonenumber}", "confAdjust": 0.95, "options" : { "maxTokensLeft": 1, "maxTokensRight": 1 } |
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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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