2023:Labeling Behavior (Behavior) - Revision history

Dgreenwood at 16:07, 2 September 2025

2025-09-02T16:07:56Z

Dgreenwood at 21:23, 12 May 2025

2025-05-12T21:23:34Z

Randallkinard at 21:38, 21 November 2024

2024-11-21T21:38:06Z

← Older revision		Revision as of 16:38, 21 November 2024
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	[[File:2023-Labeling Behavior-Label Match Example 04.png]]		[[File:2023-Labeling Behavior-Label Match Example 04.png]]
	\|}		\|}

	~~== Glossary ==~~
	~~<u><big>'''Batch Folder'''</big></u>: {{#lst:Glossary\|Batch Folder}}~~

	~~<u><big>'''Batch Process Step'''</big></u>: {{#lst:Glossary\|Batch Process Step}}~~

	~~<u><big>'''Batch Process'''</big></u>: {{#lst:Glossary\|Batch Process}}~~

	~~<u><big>'''Batch'''</big></u>: {{#lst:Glossary\|Batch}}~~

	~~<u><big>'''Behavior'''</big></u>: {{#lst:Glossary\|Behavior}}~~

	~~<u><big>'''Box'''</big></u>: {{#lst:Glossary\|Box}}~~

	~~<u><big>'''Classification Method'''</big></u>: {{#lst:Glossary\|Classification Method}}~~

	~~<u><big>'''Classification'''</big></u>: {{#lst:Glossary\|Classification}}~~

	~~<u><big>'''Classify'''</big></u>: {{#lst:Glossary\|Classify}}~~

	~~<u><big>'''Constrained Wrap'''</big></u>: {{#lst:Glossary\|Constrained Wrap}}~~

	~~<u><big>'''Content Model'''</big></u>: {{#lst:Glossary\|Content Model}}~~

	~~<u><big>'''Content Type'''</big></u>: {{#lst:Glossary\|Content Type}}~~

	~~<u><big>'''Data Column'''</big></u>: {{#lst:Glossary\|Data Column}}~~

	~~<u><big>'''Data Element'''</big></u>: {{#lst:Glossary\|Data Element}}~~

	~~<u><big>'''Data Field'''</big></u>: {{#lst:Glossary\|Data Field}}~~

	~~<u><big>'''Data Model'''</big></u>: {{#lst:Glossary\|Data Model}}~~

	~~<u><big>'''Data Section'''</big></u>: {{#lst:Glossary\|Data Section}}~~

	~~<u><big>'''Data Table'''</big></u>: {{#lst:Glossary\|Data Table}}~~

	~~<u><big>'''Data Type'''</big></u>: {{#lst:Glossary\|Data Type}}~~

	~~<u><big>'''Document Type'''</big></u>: {{#lst:Glossary\|Document Type}}~~

	~~<u><big>'''Document Viewer'''</big></u>: {{#lst:Glossary\|Document Viewer}}~~

	~~<u><big>'''Execute'''</big></u>: {{#lst:Glossary\|Execute}}~~

	~~<u><big>'''Extract'''</big></u>: {{#lst:Glossary\|Extract}}~~

	~~<u><big>'''Extractor Type'''</big></u>: {{#lst:Glossary\|Extractor Type}}~~

	~~<u><big>'''Fluid Layout'''</big></u>: {{#lst:Glossary\|Fluid Layout}}~~

	~~<u><big>'''Fuzzy RegEx'''</big></u>: {{#lst:Glossary\|Fuzzy RegEx}}~~

	~~<u><big>'''Image Processing'''</big></u>: {{#lst:Glossary\|Image Processing}}~~

	~~<u><big>'''Image Processing'''</big></u>: {{#lst:Glossary\|Image Processing}}~~

	~~<u><big>'''IP Command'''</big></u>: {{#lst:Glossary\|IP Command}}~~

	~~<u><big>'''IP Profile'''</big></u>: {{#lst:Glossary\|IP Profile}}~~

	~~<u><big>'''Label Match'''</big></u>: {{#lst:Glossary\|Label Match}}~~

	~~<u><big>'''Labeled Value'''</big></u>: {{#lst:Glossary\|Labeled Value}}~~

	~~<u><big>'''Labeling Behavior'''</big></u>: {{#lst:Glossary\|Labeling Behavior}}~~

	~~<u><big>'''Labelset-Based'''</big></u>: {{#lst:Glossary\|Labelset-Based}}~~

	~~<u><big>'''Layout Data'''</big></u>: {{#lst:Glossary\|Layout Data}}~~

	~~<u><big>'''Lexical'''</big></u>: {{#lst:Glossary\|Lexical}}~~

	~~<u><big>'''Lexicon'''</big></u>: {{#lst:Glossary\|Lexicon}}~~

	~~<u><big>'''Line Removal'''</big></u>: {{#lst:Glossary\|Line Removal}}~~

	~~<u><big>'''List Match'''</big></u>: {{#lst:Glossary\|List Match}}~~

	~~<u><big>'''Nested Table'''</big></u>: {{#lst:Glossary\|Nested Table}}~~

	~~<u><big>'''Node Tree'''</big></u>: {{#lst:Glossary\|Node Tree}}~~

	~~<u><big>'''OCR'''</big></u>: {{#lst:Glossary\|OCR}}~~

	~~<u><big>'''Ordered Array'''</big></u>: {{#lst:Glossary\|Ordered Array}}~~

	~~<u><big>'''Overrides'''</big></u>: {{#lst:Glossary\|Overrides}}~~

	~~<u><big>'''Pattern Match'''</big></u>: {{#lst:Glossary\|Pattern Match}}~~

	~~<u><big>'''Project'''</big></u>: {{#lst:Glossary\|Project}}~~

	~~<u><big>'''Recognize'''</big></u>: {{#lst:Glossary\|Recognize}}~~

	~~<u><big>'''Reference'''</big></u>: {{#lst:Glossary\|Reference}}~~

	~~<u><big>'''Row Match'''</big></u>: {{#lst:Glossary\|Row Match}}~~

	~~<u><big>'''Scope'''</big></u>: {{#lst:Glossary\|Scope}}~~

	~~<u><big>'''Service'''</big></u>: {{#lst:Glossary\|Service}}~~

	~~<u><big>'''Tabular Layout'''</big></u>: {{#lst:Glossary\|Tabular Layout}}~~

	~~<u><big>'''Test Batch'''</big></u>: {{#lst:Glossary\|Test Batch}}~~

	~~<u><big>'''Transaction Detection'''</big></u>: {{#lst:Glossary\|Transaction Detection}}~~

	~~<u><big>'''Value Reader'''</big></u>: {{#lst:Glossary\|Value Reader}}~~

	~~<u><big>'''Vertical Wrap'''</big></u>: {{#lst:Glossary\|Vertical Wrap}}~~

Dgreenwood: /* How To Use label sets for sectional extraction */

2024-09-18T20:07:25Z

How To Use label sets for sectional extraction

← Older revision		Revision as of 15:07, 18 September 2024
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	<section end="Fluid Layout" />		<section end="Fluid Layout" />

	== How To Use label sets for ~~sectional~~ extraction ==		== How To Use label sets for section extraction ==

	There are two Label Set aware '''''Extract Methods''''' for '''Data Sections.'''		There are two Label Set aware '''''Extract Methods''''' for '''Data Sections.'''

Dgreenwood: /* Set Data Section's Extract Method to Nested Table */

2024-09-18T20:07:05Z

Set Data Section's Extract Method to Nested Table

← Older revision		Revision as of 15:07, 18 September 2024
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	[[File:2023-Labeling Behavior-Nested Tables 02 Extract Method to Nested Table 01.png]]		[[File:2023-Labeling Behavior-Nested Tables 02 Extract Method to Nested Table 01.png]]
	\|}		\|}
	~~</tab>~~
	~~<tab name="Configure the Data Table" style="margin:20px">~~
	==== Configure the Data Table ====		==== Configure the Data Table ====

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	\|}		\|}

	~~</tab>~~
	~~<tab name="Add the Data Sections Footer Label" style="margin:20px">~~
	==== Add the Data Section's Footer Label ====		==== Add the Data Section's Footer Label ====

Dgreenwood: /* Add the Data Section's Footer Label */

2024-09-18T20:06:44Z

Add the Data Section's Footer Label

← Older revision		Revision as of 15:06, 18 September 2024
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	</tab>		</tab>
	<tab name="Add the Data Sections Footer Label" style="margin:20px">		<tab name="Add the Data Sections Footer Label" style="margin:20px">
	=== Add the Data Section's Footer Label ===		==== Add the Data Section's Footer Label ====

	In order for the '''''Nested Table''''' method to properly section out the document, you must assign a '''''Footer''''' label in the '''Document Type's''' Label Set for the '''Data Section'''. This will give '''Grooper''' an awareness of where the section should ''stop'' (ultimately allowing another section to ''start''). In our case, we can use the text label "Totals". At the end of every table/section there is this "Totals" line totaling up various columns in the table. Since this label is present at the end of every section, we can collect it as the '''Data Section's''' '''''Footer''''' label, which the '''''Nested Table''''' method will then use to establish where each section instance ends.		In order for the '''''Nested Table''''' method to properly section out the document, you must assign a '''''Footer''''' label in the '''Document Type's''' Label Set for the '''Data Section'''. This will give '''Grooper''' an awareness of where the section should ''stop'' (ultimately allowing another section to ''start''). In our case, we can use the text label "Totals". At the end of every table/section there is this "Totals" line totaling up various columns in the table. Since this label is present at the end of every section, we can collect it as the '''Data Section's''' '''''Footer''''' label, which the '''''Nested Table''''' method will then use to establish where each section instance ends.

Dgreenwood: /* How To Use Label Sets for Sectional Extraction */

2024-09-18T20:06:27Z

How To Use Label Sets for Sectional Extraction

← Older revision		Revision as of 15:06, 18 September 2024
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	<section end="Fluid Layout" />		<section end="Fluid Layout" />

	== How To Use ~~Label Sets~~ for ~~Sectional Extraction~~ ==		== How To Use label sets for sectional extraction ==

	There are two Label Set aware '''''Extract Methods''''' for '''Data Sections.'''		There are two Label Set aware '''''Extract Methods''''' for '''Data Sections.'''
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	The '''''Nested Table''''' method is a much more niche section extraction method. It produces section instances using repeating tables, nested within each section. This can be a highly effective way to target sections for certain use cases, such as medical EOB (explanation of benefits) forms.		The '''''Nested Table''''' method is a much more niche section extraction method. It produces section instances using repeating tables, nested within each section. This can be a highly effective way to target sections for certain use cases, such as medical EOB (explanation of benefits) forms.

	=== Label ~~Sets~~ and the Transaction Detection ~~Method~~ ===		=== Label sets and the Transaction Detection method ===
	<section begin="Transaction Detection Label Sets" />		<section begin="Transaction Detection Label Sets" />
	==== About Transaction Detection ====		==== About Transaction Detection ====
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	\|}		\|}

	==== Configuring Transaction Detection with ~~Label Sets~~ ====		==== Configuring Transaction Detection with label sets ====

	Now that we understand the basics of the ''Transaction Detection'' method, we can look at how this sectioning method interacts with the ''Labeling Behavior''. Its behavior is wildly different if a '''''Header''''' label is collected for the '''Data Section'''. Assuming you can collect a '''''Header''''' label for the '''Data Section''', it is so different that a '''''Binding Field''''' is not even necessary to produce the section instances.		Now that we understand the basics of the ''Transaction Detection'' method, we can look at how this sectioning method interacts with the ''Labeling Behavior''. Its behavior is wildly different if a '''''Header''''' label is collected for the '''Data Section'''. Assuming you can collect a '''''Header''''' label for the '''Data Section''', it is so different that a '''''Binding Field''''' is not even necessary to produce the section instances.
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	<section end="Transaction Detection Label Sets" />		<section end="Transaction Detection Label Sets" />

	=== Label Sets and the Nested Table ~~Method~~ ===		=== Label Sets and the Nested Table method ===
	<section begin="nested_table_method" />		<section begin="nested_table_method" />
	[[File:Nested-table-extraction- eob-table-example.png\|600px\|right]]		[[File:Nested-table-extraction- eob-table-example.png\|600px\|right]]
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	</tab>		</tab>
	<tab name="Add the Data Sections Footer Label" style="margin:20px">		<tab name="Add the Data Sections Footer Label" style="margin:20px">
	=== Add the Data ~~Sections~~ Footer Label ===		=== Add the Data Section's Footer Label ===

	In order for the '''''Nested Table''''' method to properly section out the document, you must assign a '''''Footer''''' label in the '''Document Type's''' Label Set for the '''Data Section'''. This will give '''Grooper''' an awareness of where the section should ''stop'' (ultimately allowing another section to ''start''). In our case, we can use the text label "Totals". At the end of every table/section there is this "Totals" line totaling up various columns in the table. Since this label is present at the end of every section, we can collect it as the '''Data Section's''' '''''Footer''''' label, which the '''''Nested Table''''' method will then use to establish where each section instance ends.		In order for the '''''Nested Table''''' method to properly section out the document, you must assign a '''''Footer''''' label in the '''Document Type's''' Label Set for the '''Data Section'''. This will give '''Grooper''' an awareness of where the section should ''stop'' (ultimately allowing another section to ''start''). In our case, we can use the text label "Totals". At the end of every table/section there is this "Totals" line totaling up various columns in the table. Since this label is present at the end of every section, we can collect it as the '''Data Section's''' '''''Footer''''' label, which the '''''Nested Table''''' method will then use to establish where each section instance ends.
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	[[File:2023-Labeling Behavior-Nested Tables 04 Data Sections Footer Label 01.png]]		[[File:2023-Labeling Behavior-Nested Tables 04 Data Sections Footer Label 01.png]]
	\|}		\|}
	==== Run Global ~~Header Detection~~ ====		==== Run Global header detection ====

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	[[File:2023-Labeling Behavior-Nested Tables 05 Run Global Header Detection 05.png]]		[[File:2023-Labeling Behavior-Nested Tables 05 Run Global Header Detection 05.png]]
	\|}		\|}
	==== Test ~~For Success~~ ====		==== Test for success ====

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5

Dgreenwood: /* Label Sets and the Nested Table Method */

2024-09-18T20:04:46Z

Label Sets and the Nested Table Method

← Older revision		Revision as of 15:04, 18 September 2024
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	\|}		\|}
	<span id="Label Sets and the Nested Table Method Anchor"></span>		<span id="Label Sets and the Nested Table Method Anchor"></span>
	~~<tabs style~~=~~"margin:20px">~~		==== Set Data Section's Extract Method to Nested Table ====
	~~<tab name="Set Data Section's Extract Method to Nested Table" style="margin:20px">~~
	=== Set Data Section's Extract Method to Nested Table ===

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	</tab>		</tab>
	<tab name="Configure the Data Table" style="margin:20px">		<tab name="Configure the Data Table" style="margin:20px">
	=== Configure the Data Table ===		==== Configure the Data Table ====

	The '''Data Table''' should be configured to collect ''all'' table rows for the full document. When configuring the '''Data Table''' and testing its results, just ensure the table accurately extracts the full document as a single table. The '''Data Section''' (using the ''Nested Table'' method) will take care of breaking out the rows into the appropriate sections.		The '''Data Table''' should be configured to collect ''all'' table rows for the full document. When configuring the '''Data Table''' and testing its results, just ensure the table accurately extracts the full document as a single table. The '''Data Section''' (using the ''Nested Table'' method) will take care of breaking out the rows into the appropriate sections.
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	[[File:2023-Labeling Behavior-Nested Tables 04 Data Sections Footer Label 01.png]]		[[File:2023-Labeling Behavior-Nested Tables 04 Data Sections Footer Label 01.png]]
	\|}		\|}
	~~</tab>~~		==== Run Global Header Detection ====
	~~<tab name~~=~~"Run Global Header Detection" style="margin:20px">~~
	=== Run Global Header Detection ===

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	[[File:2023-Labeling Behavior-Nested Tables 05 Run Global Header Detection 05.png]]		[[File:2023-Labeling Behavior-Nested Tables 05 Run Global Header Detection 05.png]]
	\|}		\|}
			==== Test For Success ====
	~~</tab>~~
	~~<tab name~~=~~"Test For Success" style="margin:20px">~~
	=== Test For Success ===

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	[[File:2023-Labeling Behavior-Nested Tables 06 Test for Success 01.png]]		[[File:2023-Labeling Behavior-Nested Tables 06 Test for Success 01.png]]
	\|}		\|}

	~~</tab>~~
	~~:[[#Label Sets and the Nested Table Method Anchor\|Click me to return to the top]]~~
	~~</tabs>~~
	<section end="nested_table_method" />		<section end="nested_table_method" />

Dgreenwood: /* Label Sets and the Transaction Detection Method */

2024-09-18T20:03:52Z

Label Sets and the Transaction Detection Method

← Older revision		Revision as of 15:03, 18 September 2024
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	=== Label Sets and the Transaction Detection Method ===		=== Label Sets and the Transaction Detection Method ===
	<section begin="Transaction Detection Label Sets" />		<section begin="Transaction Detection Label Sets" />
	~~<tabs style~~=~~"margin:20px">~~		==== About Transaction Detection ====
	~~<tab name="About Transaction Detection" style="margin:20px">~~
	=== About Transaction Detection ===

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	It is best to understand how this sectioning method works ''without'' Label Sets before we delve into how it works with them.		It is best to understand how this sectioning method works ''without'' Label Sets before we delve into how it works with them.
	\|}		\|}
	~~</tab>~~		==== Configuring Transaction Detection with Binding Fields ====
	~~<tab name~~=~~"Configuring Transaction Detection with Binding Fields" style="margin:20px">~~
	=== Configuring Transaction Detection with Binding Fields ===

	{\|cellpadding=10 cellspacing=5		{\|cellpadding=10 cellspacing=5
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	[[File:2023-Labeling Behavior-Transaction Detection with Binding Fields 07.png]]		[[File:2023-Labeling Behavior-Transaction Detection with Binding Fields 07.png]]
	\|}		\|}
	~~</tab>~~

	~~<tab name="Configuring Transaction Detection with Label Sets" style="margin:20px">~~
	~~=== Configuring Transaction Detection with Label Sets ===~~

			==== Configuring Transaction Detection with Label Sets ====

	Now that we understand the basics of the ''Transaction Detection'' method, we can look at how this sectioning method interacts with the ''Labeling Behavior''. Its behavior is wildly different if a '''''Header''''' label is collected for the '''Data Section'''. Assuming you can collect a '''''Header''''' label for the '''Data Section''', it is so different that a '''''Binding Field''''' is not even necessary to produce the section instances.		Now that we understand the basics of the ''Transaction Detection'' method, we can look at how this sectioning method interacts with the ''Labeling Behavior''. Its behavior is wildly different if a '''''Header''''' label is collected for the '''Data Section'''. Assuming you can collect a '''''Header''''' label for the '''Data Section''', it is so different that a '''''Binding Field''''' is not even necessary to produce the section instances.
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	[[File:2023-Labeling Behavior-Transaction Detection with Label Sets 04.png]]		[[File:2023-Labeling Behavior-Transaction Detection with Label Sets 04.png]]
	\|}		\|}

	~~</tab>~~
	~~:[[#Label Sets and the Transaction Detection Method\|Click me to return to the top]]~~
	~~</tabs>~~

	<section end="Transaction Detection Label Sets" />		<section end="Transaction Detection Label Sets" />

Dgreenwood: /* Additional Information */

2024-09-18T20:02:32Z

Additional Information

Show changes

← Older revision		Revision as of 16:38, 21 November 2024
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	[[File:2023-Labeling Behavior-Label Match Example 04.png]]		[[File:2023-Labeling Behavior-Label Match Example 04.png]]
	\|}		\|}

	~~== Glossary ==~~
	~~<u><big>'''Batch Folder'''</big></u>: {{#lst:Glossary\|Batch Folder}}~~

	~~<u><big>'''Batch Process Step'''</big></u>: {{#lst:Glossary\|Batch Process Step}}~~

	~~<u><big>'''Batch Process'''</big></u>: {{#lst:Glossary\|Batch Process}}~~

	~~<u><big>'''Batch'''</big></u>: {{#lst:Glossary\|Batch}}~~

	~~<u><big>'''Behavior'''</big></u>: {{#lst:Glossary\|Behavior}}~~

	~~<u><big>'''Box'''</big></u>: {{#lst:Glossary\|Box}}~~

	~~<u><big>'''Classification Method'''</big></u>: {{#lst:Glossary\|Classification Method}}~~

	~~<u><big>'''Classification'''</big></u>: {{#lst:Glossary\|Classification}}~~

	~~<u><big>'''Classify'''</big></u>: {{#lst:Glossary\|Classify}}~~

	~~<u><big>'''Constrained Wrap'''</big></u>: {{#lst:Glossary\|Constrained Wrap}}~~

	~~<u><big>'''Content Model'''</big></u>: {{#lst:Glossary\|Content Model}}~~

	~~<u><big>'''Content Type'''</big></u>: {{#lst:Glossary\|Content Type}}~~

	~~<u><big>'''Data Column'''</big></u>: {{#lst:Glossary\|Data Column}}~~

	~~<u><big>'''Data Element'''</big></u>: {{#lst:Glossary\|Data Element}}~~

	~~<u><big>'''Data Field'''</big></u>: {{#lst:Glossary\|Data Field}}~~

	~~<u><big>'''Data Model'''</big></u>: {{#lst:Glossary\|Data Model}}~~

	~~<u><big>'''Data Section'''</big></u>: {{#lst:Glossary\|Data Section}}~~

	~~<u><big>'''Data Table'''</big></u>: {{#lst:Glossary\|Data Table}}~~

	~~<u><big>'''Data Type'''</big></u>: {{#lst:Glossary\|Data Type}}~~

	~~<u><big>'''Document Type'''</big></u>: {{#lst:Glossary\|Document Type}}~~

	~~<u><big>'''Document Viewer'''</big></u>: {{#lst:Glossary\|Document Viewer}}~~

	~~<u><big>'''Execute'''</big></u>: {{#lst:Glossary\|Execute}}~~

	~~<u><big>'''Extract'''</big></u>: {{#lst:Glossary\|Extract}}~~

	~~<u><big>'''Extractor Type'''</big></u>: {{#lst:Glossary\|Extractor Type}}~~

	~~<u><big>'''Fluid Layout'''</big></u>: {{#lst:Glossary\|Fluid Layout}}~~

	~~<u><big>'''Fuzzy RegEx'''</big></u>: {{#lst:Glossary\|Fuzzy RegEx}}~~

	~~<u><big>'''Image Processing'''</big></u>: {{#lst:Glossary\|Image Processing}}~~

	~~<u><big>'''Image Processing'''</big></u>: {{#lst:Glossary\|Image Processing}}~~

	~~<u><big>'''IP Command'''</big></u>: {{#lst:Glossary\|IP Command}}~~

	~~<u><big>'''IP Profile'''</big></u>: {{#lst:Glossary\|IP Profile}}~~

	~~<u><big>'''Label Match'''</big></u>: {{#lst:Glossary\|Label Match}}~~

	~~<u><big>'''Labeled Value'''</big></u>: {{#lst:Glossary\|Labeled Value}}~~

	~~<u><big>'''Labeling Behavior'''</big></u>: {{#lst:Glossary\|Labeling Behavior}}~~

	~~<u><big>'''Labelset-Based'''</big></u>: {{#lst:Glossary\|Labelset-Based}}~~

	~~<u><big>'''Layout Data'''</big></u>: {{#lst:Glossary\|Layout Data}}~~

	~~<u><big>'''Lexical'''</big></u>: {{#lst:Glossary\|Lexical}}~~

	~~<u><big>'''Lexicon'''</big></u>: {{#lst:Glossary\|Lexicon}}~~

	~~<u><big>'''Line Removal'''</big></u>: {{#lst:Glossary\|Line Removal}}~~

	~~<u><big>'''List Match'''</big></u>: {{#lst:Glossary\|List Match}}~~

	~~<u><big>'''Nested Table'''</big></u>: {{#lst:Glossary\|Nested Table}}~~

	~~<u><big>'''Node Tree'''</big></u>: {{#lst:Glossary\|Node Tree}}~~

	~~<u><big>'''OCR'''</big></u>: {{#lst:Glossary\|OCR}}~~

	~~<u><big>'''Ordered Array'''</big></u>: {{#lst:Glossary\|Ordered Array}}~~

	~~<u><big>'''Overrides'''</big></u>: {{#lst:Glossary\|Overrides}}~~

	~~<u><big>'''Pattern Match'''</big></u>: {{#lst:Glossary\|Pattern Match}}~~

	~~<u><big>'''Project'''</big></u>: {{#lst:Glossary\|Project}}~~

	~~<u><big>'''Recognize'''</big></u>: {{#lst:Glossary\|Recognize}}~~

	~~<u><big>'''Reference'''</big></u>: {{#lst:Glossary\|Reference}}~~

	~~<u><big>'''Row Match'''</big></u>: {{#lst:Glossary\|Row Match}}~~

	~~<u><big>'''Scope'''</big></u>: {{#lst:Glossary\|Scope}}~~

	~~<u><big>'''Service'''</big></u>: {{#lst:Glossary\|Service}}~~

	~~<u><big>'''Tabular Layout'''</big></u>: {{#lst:Glossary\|Tabular Layout}}~~

	~~<u><big>'''Test Batch'''</big></u>: {{#lst:Glossary\|Test Batch}}~~

	~~<u><big>'''Transaction Detection'''</big></u>: {{#lst:Glossary\|Transaction Detection}}~~

	~~<u><big>'''Value Reader'''</big></u>: {{#lst:Glossary\|Value Reader}}~~

	~~<u><big>'''Vertical Wrap'''</big></u>: {{#lst:Glossary\|Vertical Wrap}}~~

← Older revision		Revision as of 11:07, 2 September 2025
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	<!---NOTE TO SELF I would like to redo the "Label ~~SEts~~ and the ~~Labeld~~ Value ~~Extractor Type~~" and "Additional Considerations When Using ~~LAbeled VAlue~~ with Label ~~SEts~~" at some point to more closely align the content with the LMS content--->		<!---NOTE TO SELF I would like to redo the "Label Sets and the Labeled Value extractor" and "Additional Considerations When Using Labeled Value with Label Sets" at some point to more closely align the content with the LMS content--->
	{{AutoVersion}}		{{AutoVersion}}

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	* Document classification - Using the '''''Labelset-Based''''' Classify Method		* Document classification - Using the '''''Labelset-Based''''' Classify Method
	* Field based data extraction - Primarily using the '''''Labeled Value''''' Extractor ~~Type~~		* Field based data extraction - Primarily using the '''''Labeled Value''''' Value Extractor
	* Tabular data extraction - Primarily using a '''Data Table''' object's '''''Tabular Layout''''' Extract Method		* Tabular data extraction - Primarily using a '''Data Table''' object's '''''Tabular Layout''''' Extract Method
	* Sectional data extraction - Primarily using a '''Data Section''' object's '''''Transaction Detection''''' Extract Method		* Sectional data extraction - Primarily using a '''Data Section''' object's '''''Transaction Detection''''' Extract Method
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	== How to use label sets for field based extraction ==		== How to use label sets for field based extraction ==

	=== Label sets and the Labeled Value ~~Extractor Type~~ ===		=== Label sets and the Labeled Value exector ===

	==== Intro to The Labeled Value extractor ====		==== Intro to The Labeled Value extractor ====

	For most static field based extraction, the '''''Labeling Behavior''''' leverages the '''''Labeled Value''''' Extractor ~~Type~~. Let's first briefly examine how '''''Labeled Value''''' works outside of the '''''Labeling Behavior''''' functionality.		For most static field based extraction, the '''''Labeling Behavior''''' leverages the '''''Labeled Value''''' Value Extractor. Let's first briefly examine how '''''Labeled Value''''' works outside of the '''''Labeling Behavior''''' functionality.

	As the name implies, '''''Labeled Value''''' extractor is designed to return labeled values. A common feature of structured forms is to divide information across a series of fields. But it's not as if you just have a bunch of data randomly strewn throughout the document. Typically, the field's value will be identified by some kind of label. These labels provide the critical context to what the data refers to.		As the name implies, '''''Labeled Value''''' extractor is designed to return labeled values. A common feature of structured forms is to divide information across a series of fields. But it's not as if you just have a bunch of data randomly strewn throughout the document. Typically, the field's value will be identified by some kind of label. These labels provide the critical context to what the data refers to.
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	Now that the '''''Static''''' label is collected, how does '''Grooper''' know to return it during extraction when the '''Extract''' activity runs? The short answer is the '''''Labeled Value''''' extractor ~~type~~ will do this for us.		Now that the '''''Static''''' label is collected, how does '''Grooper''' know to return it during extraction when the '''Extract''' activity runs? The short answer is the '''''Labeled Value''''' extractor will do this for us.

	With "Factura Technology Corp" collected as a '''''Static''''' label, and the "Vendor Name" '''Data Field''' configured to utilize the '''''Labeled Value''''' extractor, it will return the '''''Static''''' label itself as the result.		With "Factura Technology Corp" collected as a '''''Static''''' label, and the "Vendor Name" '''Data Field''' configured to utilize the '''''Labeled Value''''' extractor, it will return the '''''Static''''' label itself as the result.

	# Here, we have the "Vendor Name" '''Data Field''' selected in the Node Tree.		# Here, we have the "Vendor Name" '''Data Field''' selected in the Node Tree.
	# The '''Data Field's''' '''''Value Extractor''''' property is set to use the '''''Labeled Value''''' extractor ~~type~~.		# The '''Data Field's''' '''''Value Extractor''''' property is set to use the '''''Labeled Value''''' extractor.
	# The '''''Labeled Value''''' extractor's '''''Label Extractor''''' and '''''Value Extractor''''' are both unconfigured.		# The '''''Labeled Value''''' extractor's '''''Label Extractor''''' and '''''Value Extractor''''' are both unconfigured.
	\|		\|
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	=== Data Element Override Utility ===		=== Data Element Override Utility ===

	Earlier in this article, we talked about using the '''''Labeled Value''''' ~~Extractor Type~~ ''without'' configuring its '''''Value Extractor'''''. Again, it is considered best practice to configure its '''''Value Extractor'''''. However, sometimes data is difficult to pattern match. For example, crafting an extractor to return people or company names can be difficult to craft. It is truly these cases why the option to leave a '''''Labeled Value''''' extractor's '''''Value Extractor''''' unconfigured is an option with Label Sets.		Earlier in this article, we talked about using the '''''Labeled Value''''' extractor ''without'' configuring its '''''Value Extractor''''' property. Again, it is considered best practice to configure its '''''Value Extractor''''' property. However, sometimes data is difficult to pattern match. For example, crafting an extractor to return people or company names can be difficult to craft. It is truly these cases why the option to leave a '''''Labeled Value''''' extractor's '''''Value Extractor''''' property unconfigured is an option with Label Sets.

	To make the best use of this functionality, Data Element Overrides are typically necessary. Indeed, because the Label Set approach is more templated in nature, Data Element Overrides can be a useful tool to fine tune extraction for one specific '''Document Type'''. In this section, we will use the "Purchase Order Number" '''Data Field''' of our "Labeling Behavior - Invoices - Model" '''Content Model''' to demonstrate this.		To make the best use of this functionality, Data Element Overrides are typically necessary. Indeed, because the Label Set approach is more templated in nature, Data Element Overrides can be a useful tool to fine tune extraction for one specific '''Document Type'''. In this section, we will use the "Purchase Order Number" '''Data Field''' of our "Labeling Behavior - Invoices - Model" '''Content Model''' to demonstrate this.
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	# Just like before, this is a duplication of the '''Data Element's''' property grid. Any adjustments you make to the '''Data Element''' will execute ''only'' for the '''Document Type''' selected. Here we have gone into the '''''Maximum Distance''''' property and deleted out the '''''Right''''' value.		# Just like before, this is a duplication of the '''Data Element's''' property grid. Any adjustments you make to the '''Data Element''' will execute ''only'' for the '''Document Type''' selected. Here we have gone into the '''''Maximum Distance''''' property and deleted out the '''''Right''''' value.
	#* For example, we can clear out the '''''Labeled Value''''' extractor's ''''''Right Maximum Distance''''' property, forcing the '''''Labeled Value''''' to only "look" for text below the label.		#* For example, we can clear out the '''''Labeled Value''''' extractor's ''''''Right Maximum Distance''''' property, forcing the '''''Labeled Value''''' to only "look" for text below the label.
	#* FYI: You can override ANY property for ANY '''Data Element'''. For example, you could use a completely different extractor ~~type~~ for a '''Data Field''' for a specified '''Document Type'''.		#* FYI: You can override ANY property for ANY '''Data Element'''. For example, you could use a completely different extractor (Extractor Node or Value Extractor) for a '''Data Field''' for a specified '''Document Type'''.
	# Click "SAVE" to save the override configuration.		# Click "SAVE" to save the override configuration.
	\|		\|
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	# In this example, a '''Value Reader''' is configured to return a small list of field labels on an invoice, using the ''Label Match'' ~~'''''~~Extractor ~~Type'''''~~.		# In this example, a '''Value Reader''' is configured to return a small list of field labels on an invoice, using the ''Label Match'' Value Extractor.
	# ''Label Match'' is selected as the '''''Extractor ~~Type~~'''''.		# ''Label Match'' is selected as the '''''Extractor'''''.
	\|		\|
	[[File:2023-Labeling Behavior-Label Match Example 01.png]]		[[File:2023-Labeling Behavior-Label Match Example 01.png]]

← Older revision		Revision as of 16:23, 12 May 2025
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	The '''''Labeling Behavior''''' functionality allows Grooper users to quickly onboard new '''Document Types''' for structured and semi-structured forms, utilizing labels as a thumbprint for classification and data extraction purposes. Once the '''''Labeling Behavior''''' is enabled, labels are identified and collected using the "Labels" tab of '''Document Types'''. These "Label Sets" can then be used for the following purposes:		The '''''Labeling Behavior''''' functionality allows Grooper users to quickly onboard new '''Document Types''' for structured and semi-structured forms, utilizing labels as a thumbprint for classification and data extraction purposes. Once the '''''Labeling Behavior''''' is enabled, labels are identified and collected using the "Labels" tab of '''Document Types'''. These "Label Sets" can then be used for the following purposes:

	* Document classification - Using the '''''Labelset-Based''''' ~~Classification~~ Method		* Document classification - Using the '''''Labelset-Based''''' Classify Method
	* Field based data extraction - Primarily using the '''''Labeled Value''''' Extractor Type		* Field based data extraction - Primarily using the '''''Labeled Value''''' Extractor Type
	* Tabular data extraction - Primarily using a '''Data Table''' object's '''''Tabular Layout''''' Extract Method		* Tabular data extraction - Primarily using a '''Data Table''' object's '''''Tabular Layout''''' Extract Method
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	<blockquote>{{#lst:Glossary\|Labelset-Based}}</blockquote>		<blockquote>{{#lst:Glossary\|Labelset-Based}}</blockquote>

	Label Sets can be used for classifying documents using the '''''Labelset-Based''''' ~~'''''Classification~~ Method~~'''''~~. For structured and semi-structured forms labels end up being a way of identifying a document. Without the field data entered, the labels are really what define the document. You know what kind of document you're looking at based on what kind of information is presented and in the case of '''''Labelset-Based''''' classification how that data is labeled. Even when those labels are very similar from one variant to the next, they end up being a thumbprint of that variant. For example, you might use '''''Labelset-Based''''' classification to create '''Document Types''' for different variations of invoices from different vendors. The information presented on each variant from each vendor will be more or less the same, and some labels will be more commonly used by different vendors (such as "Invoice Number"). However, if there is enough variation in the ''set'' of labels, you can easily differentiate an invoice from one vendor verses another just based on the variation in labels.		Label Sets can be used for classifying documents using the '''''Labelset-Based''''' Classify Method. For structured and semi-structured forms labels end up being a way of identifying a document. Without the field data entered, the labels are really what define the document. You know what kind of document you're looking at based on what kind of information is presented and in the case of '''''Labelset-Based''''' classification how that data is labeled. Even when those labels are very similar from one variant to the next, they end up being a thumbprint of that variant. For example, you might use '''''Labelset-Based''''' classification to create '''Document Types''' for different variations of invoices from different vendors. The information presented on each variant from each vendor will be more or less the same, and some labels will be more commonly used by different vendors (such as "Invoice Number"). However, if there is enough variation in the ''set'' of labels, you can easily differentiate an invoice from one vendor verses another just based on the variation in labels.

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	So we might have five '''Data Fields''' in our '''Data Model''', one for each piece of information. We'd also collect one label for each '''Data Field''' as well.		So we might have five '''Data Fields''' in our '''Data Model''', one for each piece of information. We'd also collect one label for each '''Data Field''' as well.

	While the data we want from these documents is the same, there is some variation in the labels used for each different document type. If we wanted to distinguish these four documents from each other by classifying using the '''''Labelset-Based''''' ~~'''''Classification Method'''''~~. This is all done measuring the similarity between the collected label sets for each '''Document Type'''.		While the data we want from these documents is the same, there is some variation in the labels used for each different document type. If we wanted to distinguish these four documents from each other by classifying using the '''''Labelset-Based''''' method. This is all done measuring the similarity between the collected label sets for each '''Document Type'''.


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	\|}		\|}
	\|}		\|}
	Using the '''''Labelset-Based''''' ~~'''''Classification Method'''''~~, unclassified documents are classified by assigning the document the '''Document Type''' whose labels are most similar. The basic concept is "similarity" is determined by how many labels are shared between the unclassified document and the label sets collected for the '''Document Types''' in your '''Content Model'''. The unclassified document is assigned the '''Document Type''' with the highest degree of similarity between matched labels and the '''Document Types'''' label sets.		Using the '''''Labelset-Based''''' method, unclassified documents are classified by assigning the document the '''Document Type''' whose labels are most similar. The basic concept is "similarity" is determined by how many labels are shared between the unclassified document and the label sets collected for the '''Document Types''' in your '''Content Model'''. The unclassified document is assigned the '''Document Type''' with the highest degree of similarity between matched labels and the '''Document Types'''' label sets.

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	=== Configuring Labelset-Based classification ===		=== Configuring Labelset-Based classification ===

	Next, we will walk through the steps required to enable and configure the ''Labelset-Based'' ~~'''''Classification~~ Method~~'''''~~, using our example set of invoice documents.		Next, we will walk through the steps required to enable and configure the ''Labelset-Based'' Classify Method, using our example set of invoice documents.

	The basic steps are as follows:		The basic steps are as follows:
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	==== Test classification ====		==== Test classification ====

	~~In general, regardless of the '''''Classification Method''''' used, one~~ of three things is going to happen to '''Batch Folders''' in a '''Batch''' during classification.		One of three things is going to happen to '''Batch Folders''' in a '''Batch''' during classification (Regardless of the classification method used).
	# The folder will be assigned the correct '''Document Type'''.		# The folder will be assigned the correct '''Document Type'''.
	# The folder will be assigned the wrong '''Document Type'''.		# The folder will be assigned the wrong '''Document Type'''.
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	The ''Labelset-Based'' ~~classification~~ method makes some assumptions about your document processing approach. It shines with structured and semi-structured forms. Labels, more or less, "stay put" on these kinds of documents. You'll see the same field labels over and over again even though the field values will change from document to document. This presumes your '''Document Types''' will be very regular (or rigid, with one Label Set very specifically corresponding to one '''Document Type'''). If you encounter a new form or variant of an existing form, you likely will need to account for it with a new '''Document Type'''.		The ''Labelset-Based'' method makes some assumptions about your document processing approach. It shines with structured and semi-structured forms. Labels, more or less, "stay put" on these kinds of documents. You'll see the same field labels over and over again even though the field values will change from document to document. This presumes your '''Document Types''' will be very regular (or rigid, with one Label Set very specifically corresponding to one '''Document Type'''). If you encounter a new form or variant of an existing form, you likely will need to account for it with a new '''Document Type'''.

	# Such is the case for this document we encountered in the [[#Label Sets and Labelset-Based Classification\|previous tutorial]].		# Such is the case for this document we encountered in the [[#Label Sets and Labelset-Based Classification\|previous tutorial]].