Merge pull request #230923 from laujan/remove-entity-reference

prmerger-automator[bot] · web-flow · commit d348de5f08e5 · 2023-03-16T00:14:16.000Z
remove entity reference
diff --git a/articles/applied-ai-services/form-recognizer/concept-analyze-document-response.md b/articles/applied-ai-services/form-recognizer/concept-analyze-document-response.md
@@ -64,7 +64,7 @@ Spans specify the logical position of each element in the overall reading order,
 
 ### Bounding Region
 
-Bounding regions describe the visual position of each element in the file. Since elements may not be visually contiguous (entities) or may cross pages (tables), the positions of most elements are described via an array of bounding regions. Each region specifies the page number (`1`-indexed) and bounding polygon.  The bounding polygon is described as a sequence of points, clockwise from the left relative to the natural orientation of the element.  For quadrilaterals, plot points are top-left, top-right, bottom-right, and bottom-left corners.  Each point is represented by its x, y coordinate in the page unit specified by the unit property.  In general, unit of measure for images is pixels while PDFs use inches.
+Bounding regions describe the visual position of each element in the file. Since elements may not be visually contiguous or may cross pages (tables), the positions of most elements are described via an array of bounding regions. Each region specifies the page number (`1`-indexed) and bounding polygon.  The bounding polygon is described as a sequence of points, clockwise from the left relative to the natural orientation of the element.  For quadrilaterals, plot points are top-left, top-right, bottom-right, and bottom-left corners.  Each point is represented by its x, y coordinate in the page unit specified by the unit property.  In general, unit of measure for images is pixels while PDFs use inches.
 
 :::image type="content" source="media/bounding-regions.png" alt-text="Screenshot of detected bounding regions example.":::
 
diff --git a/articles/applied-ai-services/form-recognizer/concept-form-recognizer-studio.md b/articles/applied-ai-services/form-recognizer/concept-form-recognizer-studio.md
@@ -31,7 +31,7 @@ The following Form Recognizer service features are available in the Studio.
 
 * **Layout**: Try out Form Recognizer's Layout feature to extract text, tables, selection marks, and structure information. Start with the [Studio Layout feature](https://formrecognizer.appliedai.azure.com/studio/layout). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [Layout overview](concept-layout.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#layout-model).
 
-* **General Documents**: Try out Form Recognizer's General Documents feature to extract key-value pairs and entities. Start with the [Studio General Documents feature](https://formrecognizer.appliedai.azure.com/studio/document). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [General Documents overview](concept-general-document.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#general-document-model).
+* **General Documents**: Try out Form Recognizer's General Documents feature to extract key-value pairs. Start with the [Studio General Documents feature](https://formrecognizer.appliedai.azure.com/studio/document). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [General Documents overview](concept-general-document.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#general-document-model).
 
 * **Prebuilt models**: Form Recognizer's prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. As an example, start with the [Studio Invoice feature](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice). Explore with sample documents and your documents. Use the interactive visualization, extracted fields list, and JSON output to understand how the feature works. See the [Models overview](concept-model-overview.md) to learn more and get started with the [Python SDK quickstart for Prebuilt Invoice](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true#prebuilt-model).
 
diff --git a/articles/applied-ai-services/form-recognizer/faq.yml b/articles/applied-ai-services/form-recognizer/faq.yml
@@ -154,8 +154,6 @@ sections:
 
           - For a PDF, coordinates are given in inches.
 
-          - You can use the bounding box returned by Form Recognizer to identify the location of recognized entities.
-
   - name: App development
     questions:
       - question: |
diff --git a/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-csharp-sdk.md b/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-csharp-sdk.md
@@ -20,7 +20,7 @@ recommendations: false
 
 In this quickstart, you use the following features to analyze and extract data and values from forms and documents:
 
-* [**General document model**](#general-document-model)—Analyze and extract text, tables, structure, key-value pairs, and named entities.
+* [**General document model**](#general-document-model)—Analyze and extract text, tables, structure, key-value pairs.
 
 * [**Layout model**](#layout-model)—Analyze and extract tables, lines, words, and selection marks like radio buttons and check boxes in documents, without the need to train a model.
 
@@ -121,7 +121,7 @@ dotnet run formrecognizer-quickstart.dll
 
 ## General document model
 
-Analyze and extract text, tables, structure, key-value pairs, and named entities.
+Analyze and extract text, tables, structure, key-value pairs.
 
 > [!div class="checklist"]
 >
diff --git a/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-java-sdk.md b/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-java-sdk.md
@@ -17,7 +17,7 @@ recommendations: false
 
 In this quickstart you'll, use the following features to analyze and extract data and values from forms and documents:
 
-* [**General document**](#general-document-model)—Analyze and extract text, tables, structure, key-value pairs, and named entities.
+* [**General document**](#general-document-model)—Analyze and extract text, tables, structure, key-value pairs.
 
 * [**Layout**](#layout-model)—Analyze and extract tables, lines, words, and selection marks like radio buttons and check boxes in documents, without the need to train a model.
 
@@ -138,7 +138,7 @@ To interact with the Form Recognizer service, you need to create an instance of
 
 ## General document model
 
-Extract text, tables, structure, key-value pairs, and named entities from documents.
+Extract text, tables, structure, and key-value pairs from documents.
 
 > [!div class="checklist"]
 >
diff --git a/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-javascript-sdk.md b/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-javascript-sdk.md
@@ -17,7 +17,7 @@ recommendations: false
 
 In this quickstart you'll, use the following features to analyze and extract data and values from forms and documents:
 
-* [**General document**](#general-document-model)—Analyze and extract key-value pairs, selection marks, and entities from documents.
+* [**General document**](#general-document-model)—Analyze and extract key-value pairs, and selection marks from documents.
 
 * [**Layout**](#layout-model)—Analyze and extract tables, lines, words, and selection marks like radio buttons and check boxes in documents, without the need to train a model.
 
@@ -102,7 +102,7 @@ To interact with the Form Recognizer service, you need to create an instance of
 
 ## General document model
 
-Extract text, tables, structure, key-value pairs, and named entities from documents.
+Extract text, tables, structure,and key-value pairs from documents.
 
 > [!div class="checklist"]
 >
@@ -184,12 +184,6 @@ Key-Value Pairs:
   Value: "Common Stock, $0.00000625 par value per share" (0.748)
 - Key  : "Outstanding as of April 24, 2020"
   Value: "7,583,440,247 shares" (0.838)
-Entities:
-- "$0.00000625" Quantity - Currency (0.8)
-- "MSFT" Organization - <none> (0.99)
-- "NASDAQ" Organization - StockExchange (0.99)
-- "2.125%" Quantity - Percentage (0.8)
-- "2021" DateTime - DateRange (0.8)
 ```
 
 To view the entire output, visit the Azure samples repository on GitHub to view the [general document model output](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/javascript/FormRecognizer/v3-javascript-sdk-general-document-output.md)
diff --git a/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-python-sdk.md b/articles/applied-ai-services/form-recognizer/quickstarts/includes/v3-python-sdk.md
@@ -17,7 +17,7 @@ recommendations: false
 
 In this quickstart you'll, use the following features to analyze and extract data and values from forms and documents:
 
-* [**General document**](#general-document-model)—Analyze and extract text, tables, structure, key-value pairs, and named entities.
+* [**General document**](#general-document-model)—Analyze and extract text, tables, structure, and key-value pairs.
 
 * [**Layout**](#layout-model)—Analyze and extract tables, lines, words, and selection marks like radio buttons and check boxes in documents, without the need to train a model.
 
@@ -77,7 +77,7 @@ To interact with the Form Recognizer service, you need to create an instance of
 
 ## General document model
 
-Extract text, tables, structure, key-value pairs, and named entities from documents.
+Extract text, tables, structure, and key-value pairs from documents.
 
 > [!div class="checklist"]
 >
diff --git a/articles/applied-ai-services/form-recognizer/quickstarts/try-form-recognizer-studio.md b/articles/applied-ai-services/form-recognizer/quickstarts/try-form-recognizer-studio.md
@@ -36,7 +36,7 @@ Prebuilt models help you add Form Recognizer features to your apps without havin
 
 #### Document analysis
 
-* [**General document**](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=document): extract text, tables, structure, key-value pairs and named entities.
+* [**General document**](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=document): extract text, tables, structure, key-value pairs.
 * [**Layout**](https://formrecognizer.appliedai.azure.com/studio/layout): extract text, tables, selection marks, and structure information from documents (PDF, TIFF) and images (JPG, PNG, BMP).
 * [**Read**](https://formrecognizer.appliedai.azure.com/studio/read): extract text lines, words, their locations, detected languages, and handwritten style if detected from documents (PDF, TIFF) and images (JPG, PNG, BMP).
 
diff --git a/articles/applied-ai-services/form-recognizer/v3-migration-guide.md b/articles/applied-ai-services/form-recognizer/v3-migration-guide.md
@@ -29,7 +29,7 @@ The `2022-08-31` API has a few updates from the preview API versions:
 * Field deleted: entities removed from the result of the general document model.
 * Field rename: documentLanguage.languageCode to locale
 * Added support for HEIF format
-* Added paragraph detection, with role classification for layout and general document models    
+* Added paragraph detection, with role classification for layout and general document models.
 * Added support for parsed address fields.
 
 ## Migrating from v2.1
@@ -224,17 +224,7 @@ Analyze response has been refactored to the following top-level results to suppo
 },
 "confidence": 0.95 // Extraction confidence
 }, ...
-], // List of extracted entities
-"entities": [
-{
-"category": "DateTime", // Primary entity category
-"subCategory": "Date", // Secondary entity category
-"content": "11/15/2019", // Entity content
-"boundingRegions": [ ... ], // Entity bounding regions
-"spans": [ ... ], // Entity spans
-"confidence": 0.99 // Extraction confidence
-}, ...
-], // List of extracted styles
+], 
 "styles": [
 {
 "isHandwritten": true, // Is content in this style handwritten?
diff --git a/articles/applied-ai-services/form-recognizer/whats-new.md b/articles/applied-ai-services/form-recognizer/whats-new.md
@@ -360,7 +360,7 @@ Form Recognizer service is updated on an ongoing basis. Bookmark this page to st
 
 * **AI quality improvements**
 
-  * [**prebuilt-read**](concept-read.md). Enhanced support for single characters, handwritten dates, amounts, names, other entities commonly found in receipts and invoices and improved processing of digital PDF documents.
+  * [**prebuilt-read**](concept-read.md). Enhanced support for single characters, handwritten dates, amounts, names, other key data commonly found in receipts and invoices and improved processing of digital PDF documents.
   * [**prebuilt-layout**](concept-layout.md). Support for better detection of cropped tables, borderless tables, and improved recognition of long spanning cells.
   * [**prebuilt-document**](concept-general-document.md). Improved value and check box detection.
   * [**custom-neural**](concept-custom-neural.md). Improved accuracy for table detection and extraction.
@@ -477,10 +477,10 @@ Form Recognizer service is updated on an ongoing basis. Bookmark this page to st
 
 * Form Recognizer v3.0 preview release introduces several new features, capabilities and enhancements:
 
-  * [**Custom neural model**](concept-custom-neural.md) or custom document model is a new custom model to extract text and selection marks from structured forms, semi-strutured and **unstructured documents**.
+  * [**Custom neural model**](concept-custom-neural.md) or custom document model is a new custom model to extract text and selection marks from structured forms, semi-structured and **unstructured documents**.
   * [**W-2 prebuilt model**](concept-w2.md) is a new prebuilt model to extract fields from W-2 forms for tax reporting and income verification scenarios.
   * [**Read**](concept-read.md) API extracts printed text lines, words, text locations, detected languages, and handwritten text, if detected.
-  * [**General document**](concept-general-document.md) pretrained model is now updated to support selection marks in addition to API  text, tables, structure, key-value pairs, and named entities from forms and documents.
+  * [**General document**](concept-general-document.md) pretrained model is now updated to support selection marks in addition to API  text, tables, structure, and key-value pairs from forms and documents.
   * [**Invoice API**](language-support.md#invoice-model) Invoice prebuilt model expands support to Spanish invoices.
   * [**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com) adds new demos for Read, W2, Hotel receipt samples, and support for training the new custom neural models.
   * [**Language Expansion**](language-support.md) Form Recognizer Read, Layout, and Custom Form add support for 42 new languages including Arabic, Hindi, and other languages using Arabic and Devanagari scripts to expand the coverage to 164 languages. Handwritten language support expands to Japanese and Korean.
@@ -544,7 +544,7 @@ Form Recognizer service is updated on an ongoing basis. Bookmark this page to st
 
 * **Form Recognizer v3.0 preview release version 4.0.0-beta.1 (2021-10-07)introduces several new features and capabilities:**
 
-  * [**General document**](concept-general-document.md) model is a new API that uses a pretrained model to extract text, tables, structure, key-value pairs, and named entities from forms and documents.
+  * [**General document**](concept-general-document.md) model is a new API that uses a pretrained model to extract text, tables, structure, and key-value pairs from forms and documents.
   * [**Hotel receipt**](concept-receipt.md) model added to prebuilt receipt processing.
   * [**Expanded fields for ID document**](concept-id-document.md) the ID model supports endorsements, restrictions, and vehicle classification extraction from US driver's licenses.
   * [**Signature field**](concept-custom.md) is a new field type in custom forms to detect the presence of a signature in a form field.
@@ -556,15 +556,15 @@ Form Recognizer service is updated on an ongoing basis. Bookmark this page to st
 
 * Form Recognizer model data extraction
 
-  | **Model**   | **Text extraction** |**Key-Value pairs** |**Selection Marks**   | **Tables**   |**Entities** |
-  | --- | :---: |:---:| :---: | :---: |:---: |
-  |General document  | ✓  |  ✓ | ✓  | ✓  | ✓  |
-  | Layout  | ✓  |   | ✓  | ✓  |   |
-  | Invoice  | ✓ | ✓  | ✓  | ✓ ||
-  |Receipt  | ✓  |   ✓ |   |  ||
-  | ID document | ✓  |   ✓  |   |   ||
-  | Business card    | ✓  |   ✓ |   |   ||
-  | Custom             |✓  |  ✓ | ✓  | ✓  | ✓  |
+  | **Model**   | **Text extraction** |**Key-Value pairs** |**Selection Marks**   | **Tables**   |
+  | --- | :---: |:---:| :---: | :---: |
+  |General document  | ✓  |  ✓ | ✓  | ✓  |
+  | Layout  | ✓  |   | ✓  | ✓  |
+  | Invoice  | ✓ | ✓  | ✓  | ✓ |
+  |Receipt  | ✓  |   ✓ |   |  |
+  | ID document | ✓  |   ✓  |   |   |
+  | Business card    | ✓  |   ✓ |   |   |
+  | Custom             |✓  |  ✓ | ✓  | ✓  |
 
 ---
 
