Azure · mssfang · Mar 8, 2023 · Mar 8, 2023
@@ -1,6 +1,6 @@
 # Release History
 
-## 5.3.0-beta.2 (Unreleased)
+## 5.3.0-beta.2 (2023-03-07)
 
 ### Features Added
 - Added the following methods for performing abstractive summarization and extractive summarization actions:
@@ -17,8 +17,6 @@
 - Removed class `BooleanResolution` and enum value `BooleanResolution` in the class `ResolutionKind`.
 - Renamed `maxSentenceCount` to `sentenceCount` in abstractive summarization.
 
-### Bugs Fixed
-
 ### Other Changes
 - Integrate synchronous workflow for sync clients so that they do not block on async client APIs. 
   It simplifies stack traces and improves debugging experience.

@@ -336,99 +336,17 @@ Please refer to the service documentation for a conceptual discussion of [entity
 ### Analyze healthcare entities
 Text Analytics for health is a containerized service that extracts and labels relevant medical information from 
 unstructured texts such as doctor's notes, discharge summaries, clinical documents, and electronic health records.
+
+- [Healthcare entities recognition][recognize_healthcare_entities_sample]
+
 For more information see [How to: Use Text Analytics for health][healthcare].
-```java readme-sample-recognizeHealthcareEntities
-List<TextDocumentInput> documents = Arrays.asList(new TextDocumentInput("0",
-    "RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM | "
-        + "CORONARY ARTERY DISEASE | Signed | DIS | Admission Date: 5/22/2001 "
-        + "Report Status: Signed Discharge Date: 4/24/2001 ADMISSION DIAGNOSIS: "
-        + "CORONARY ARTERY DISEASE. HISTORY OF PRESENT ILLNESS: "
-        + "The patient is a 54-year-old gentleman with a history of progressive angina over the past"
-        + " several months. The patient had a cardiac catheterization in July of this year revealing total"
-        + " occlusion of the RCA and 50% left main disease , with a strong family history of coronary"
-        + " artery disease with a brother dying at the age of 52 from a myocardial infarction and another"
-        + " brother who is status post coronary artery bypass grafting. The patient had a stress"
-        + " echocardiogram done on July , 2001 , which showed no wall motion abnormalities,"
-        + " but this was a difficult study due to body habitus. The patient went for six minutes with"
-        + " minimal ST depressions in the anterior lateral leads , thought due to fatigue and wrist pain,"
-        + " his anginal equivalent. Due to the patient's increased symptoms and family history and"
-        + " history left main disease with total occasional of his RCA was referred"
-        + " for revascularization with open heart surgery."
-));
-AnalyzeHealthcareEntitiesOptions options = new AnalyzeHealthcareEntitiesOptions().setIncludeStatistics(true);
-SyncPoller<AnalyzeHealthcareEntitiesOperationDetail, AnalyzeHealthcareEntitiesPagedIterable>
-    syncPoller = textAnalyticsClient.beginAnalyzeHealthcareEntities(documents, options, Context.NONE);
-syncPoller.waitForCompletion();
-syncPoller.getFinalResult().forEach(
-    analyzeHealthcareEntitiesResultCollection -> analyzeHealthcareEntitiesResultCollection.forEach(
-        healthcareEntitiesResult -> {
-            System.out.println("Document entities: ");
-            AtomicInteger ct = new AtomicInteger();
-            healthcareEntitiesResult.getEntities().forEach(healthcareEntity -> {
-                System.out.printf("\ti = %d, Text: %s, category: %s, subcategory: %s, confidence score: %f.%n",
-                    ct.getAndIncrement(), healthcareEntity.getText(), healthcareEntity.getCategory(),
-                    healthcareEntity.getSubcategory(), healthcareEntity.getConfidenceScore());
-                IterableStream<EntityDataSource> healthcareEntityDataSources =
-                    healthcareEntity.getDataSources();
-                if (healthcareEntityDataSources != null) {
-                    healthcareEntityDataSources.forEach(healthcareEntityLink -> System.out.printf(
-                        "\t\tEntity ID in data source: %s, data source: %s.%n",
-                        healthcareEntityLink.getEntityId(), healthcareEntityLink.getName()));
-                }
-            });
-            // Healthcare entity relation groups
-            healthcareEntitiesResult.getEntityRelations().forEach(entityRelation -> {
-                System.out.printf("\tRelation type: %s.%n", entityRelation.getRelationType());
-                entityRelation.getRoles().forEach(role -> {
-                    final HealthcareEntity entity = role.getEntity();
-                    System.out.printf("\t\tEntity text: %s, category: %s, role: %s.%n",
-                        entity.getText(), entity.getCategory(), role.getName());
-                });
-                System.out.printf("\tRelation confidence score: %f.%n", entityRelation.getConfidenceScore());
-            });
-        }));
-```
 
 ### Custom entities recognition
 Custom NER is one of the custom features offered by Azure Cognitive Service for Language. It is a cloud-based API 
 service that applies machine-learning intelligence to enable you to build custom models for custom named entity
 recognition tasks.
 
-```java readme-sample-custom-entities-recognition
-List<String> documents = new ArrayList<>();
-documents.add(
-    "A recent report by the Government Accountability Office (GAO) found that the dramatic increase "
-        + "in oil and natural gas development on federal lands over the past six years has stretched the"
-        + " staff of the BLM to a point that it has been unable to meet its environmental protection "
-        + "responsibilities.");
-documents.add(
-    "David Schmidt, senior vice president--Food Safety, International Food"
-        + " Information Council (IFIC), Washington, D.C., discussed the physical activity component."
-);
-
-// See the service documentation for regional support and how to train a model to recognize the custom entities,
-// see https://aka.ms/azsdk/textanalytics/customentityrecognition
-SyncPoller<RecognizeCustomEntitiesOperationDetail, RecognizeCustomEntitiesPagedIterable> syncPoller =
-    textAnalyticsClient.beginRecognizeCustomEntities(documents, "{project_name}", "{deployment_name}");
-syncPoller.waitForCompletion();
-syncPoller.getFinalResult().forEach(documentsResults -> {
-    System.out.printf("Project name: %s, deployment name: %s.%n",
-        documentsResults.getProjectName(), documentsResults.getDeploymentName());
-    for (RecognizeEntitiesResult documentResult : documentsResults) {
-        System.out.println("Document ID: " + documentResult.getId());
-        if (!documentResult.isError()) {
-            for (CategorizedEntity entity : documentResult.getEntities()) {
-                System.out.printf(
-                    "\tText: %s, category: %s, confidence score: %f.%n",
-                    entity.getText(), entity.getCategory(), entity.getConfidenceScore());
-            }
-        } else {
-            System.out.printf("\tCannot recognize custom entities. Error: %s%n",
-                documentResult.getError().getMessage());
-        }
-    }
-});
-```
+- [Custom entities recognition][recognize_custom_entities_sample]
 
 For more information see [How to use: Custom Entities Recognition][custom_entities_recognition_overview].
 
@@ -437,76 +355,9 @@ Custom text classification is one of the custom features offered by Azure Cognit
 cloud-based API service that applies machine-learning intelligence to enable you to build custom models for text 
 classification tasks.
 
-- Single label classification
-```java readme-sample-single-label-classification
-List<String> documents = new ArrayList<>();
-documents.add(
-    "A recent report by the Government Accountability Office (GAO) found that the dramatic increase "
-        + "in oil and natural gas development on federal lands over the past six years has stretched the"
-        + " staff of the BLM to a point that it has been unable to meet its environmental protection "
-        + "responsibilities.");
-documents.add(
-    "David Schmidt, senior vice president--Food Safety, International Food"
-        + " Information Council (IFIC), Washington, D.C., discussed the physical activity component."
-);
-documents.add(
-    "I need a reservation for an indoor restaurant in China. Please don't stop the music. Play music "
-        + "and add it to my playlist"
-);
-
-// See the service documentation for regional support and how to train a model to classify your documents,
-// see https://aka.ms/azsdk/textanalytics/customfunctionalities
-SyncPoller<ClassifyDocumentOperationDetail, ClassifyDocumentPagedIterable> syncPoller =
-    textAnalyticsClient.beginSingleLabelClassify(documents, "{project_name}", "{deployment_name}");
-syncPoller.waitForCompletion();
-syncPoller.getFinalResult().forEach(documentsResults -> {
-    System.out.printf("Project name: %s, deployment name: %s.%n",
-        documentsResults.getProjectName(), documentsResults.getDeploymentName());
-    for (ClassifyDocumentResult documentResult : documentsResults) {
-        System.out.println("Document ID: " + documentResult.getId());
-        if (!documentResult.isError()) {
-            for (ClassificationCategory classification : documentResult.getClassifications()) {
-                System.out.printf("\tCategory: %s, confidence score: %f.%n",
-                    classification.getCategory(), classification.getConfidenceScore());
-            }
-        } else {
-            System.out.printf("\tCannot classify category of document. Error: %s%n",
-                documentResult.getError().getMessage());
-        }
-    }
-});
-```
-
-- Multi label classification
-```java readme-sample-multi-label-classification
-List<String> documents = new ArrayList<>();
-documents.add(
-    "I need a reservation for an indoor restaurant in China. Please don't stop the music."
-        + " Play music and add it to my playlist"
-);
+- [Single label classification][single_label_classification_sample]
 
-// See the service documentation for regional support and how to train a model to classify your documents,
-// see https://aka.ms/azsdk/textanalytics/customfunctionalities
-SyncPoller<ClassifyDocumentOperationDetail, ClassifyDocumentPagedIterable> syncPoller =
-    textAnalyticsClient.beginMultiLabelClassify(documents, "{project_name}", "{deployment_name}");
-syncPoller.waitForCompletion();
-syncPoller.getFinalResult().forEach(documentsResults -> {
-    System.out.printf("Project name: %s, deployment name: %s.%n",
-        documentsResults.getProjectName(), documentsResults.getDeploymentName());
-    for (ClassifyDocumentResult documentResult : documentsResults) {
-        System.out.println("Document ID: " + documentResult.getId());
-        if (!documentResult.isError()) {
-            for (ClassificationCategory classification : documentResult.getClassifications()) {
-                System.out.printf("\tCategory: %s, confidence score: %f.%n",
-                    classification.getCategory(), classification.getConfidenceScore());
-            }
-        } else {
-            System.out.printf("\tCannot classify category of document. Error: %s%n",
-                documentResult.getError().getMessage());
-        }
-    }
-});
-```
+- [Multi label classification][multi_label_classification_sample]
 
 For more information see [How to use: Custom Text Classification][custom_text_classification_overview].
 
@@ -526,58 +377,9 @@ set of documents. Currently, the supported features are:
 - Abstractive Text Summarization (API version 2022-10-01-preview and newer)
 - Extractive Text Summarization (API version 2022-10-01-preview and newer)
 
-```java readme-sample-analyzeActions
-    List<TextDocumentInput> documents = Arrays.asList(
-        new TextDocumentInput("0",
-            "We went to Contoso Steakhouse located at midtown NYC last week for a dinner party, and we adore"
-                + " the spot! They provide marvelous food and they have a great menu. The chief cook happens to be"
-                + " the owner (I think his name is John Doe) and he is super nice, coming out of the kitchen and "
-                + "greeted us all. We enjoyed very much dining in the place! The Sirloin steak I ordered was tender"
-                + " and juicy, and the place was impeccably clean. You can even pre-order from their online menu at"
-                + " www.contososteakhouse.com, call 312-555-0176 or send email to [email protected]! The"
-                + " only complaint I have is the food didn't come fast enough. Overall I highly recommend it!")
-    );
-
-    SyncPoller<AnalyzeActionsOperationDetail, AnalyzeActionsResultPagedIterable> syncPoller =
-        textAnalyticsClient.beginAnalyzeActions(documents,
-            new TextAnalyticsActions().setDisplayName("{tasks_display_name}")
-                .setExtractKeyPhrasesActions(new ExtractKeyPhrasesAction())
-                .setRecognizePiiEntitiesActions(new RecognizePiiEntitiesAction()),
-            new AnalyzeActionsOptions().setIncludeStatistics(false),
-            Context.NONE);
-    syncPoller.waitForCompletion();
-    syncPoller.getFinalResult().forEach(analyzeActionsResult -> {
-        System.out.println("Key phrases extraction action results:");
-        analyzeActionsResult.getExtractKeyPhrasesResults().forEach(actionResult -> {
-            AtomicInteger counter = new AtomicInteger();
-            if (!actionResult.isError()) {
-                for (ExtractKeyPhraseResult extractKeyPhraseResult : actionResult.getDocumentsResults()) {
-                    System.out.printf("%n%s%n", documents.get(counter.getAndIncrement()));
-                    System.out.println("Extracted phrases:");
-                    extractKeyPhraseResult.getKeyPhrases()
-                        .forEach(keyPhrases -> System.out.printf("\t%s.%n", keyPhrases));
-                }
-            }
-        });
-        System.out.println("PII entities recognition action results:");
-        analyzeActionsResult.getRecognizePiiEntitiesResults().forEach(actionResult -> {
-            AtomicInteger counter = new AtomicInteger();
-            if (!actionResult.isError()) {
-                for (RecognizePiiEntitiesResult entitiesResult : actionResult.getDocumentsResults()) {
-                    System.out.printf("%n%s%n", documents.get(counter.getAndIncrement()));
-                    PiiEntityCollection piiEntityCollection = entitiesResult.getEntities();
-                    System.out.printf("Redacted Text: %s%n", piiEntityCollection.getRedactedText());
-                    piiEntityCollection.forEach(entity -> System.out.printf(
-                        "Recognized Personally Identifiable Information entity: %s, entity category: %s, "
-                            + "entity subcategory: %s, offset: %s, confidence score: %f.%n",
-                        entity.getText(), entity.getCategory(), entity.getSubcategory(), entity.getOffset(),
-                        entity.getConfidenceScore()));
-                }
-            }
-        });
-    });
-}
-```
+
+Sample: [Multiple action analysis][multiple_actions_analysis_sample]
+
 For more examples, such as asynchronous samples, refer to [here][samples_readme].
 
 ## Troubleshooting
@@ -673,15 +475,20 @@ This project has adopted the [Microsoft Open Source Code of Conduct][coc]. For m
 [LogLevels]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/core/azure-core/src/main/java/com/azure/core/util/logging/ClientLogger.java
 
 [samples_readme]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/README.md
-[detect_language_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/DetectLanguageBatchDocuments.java
+[abstractive_summary_action_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/AbstractiveSummarization.java
 [analyze_sentiment_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/AnalyzeSentimentBatchDocuments.java
 [analyze_sentiment_with_opinion_mining_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/AnalyzeSentimentWithOpinionMining.java
+[detect_language_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/DetectLanguageBatchDocuments.java
+[dynamic_classification_sample]:  https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/DynamicClassifyBatchDocuments.java
 [extract_key_phrases_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/ExtractKeyPhrasesBatchDocuments.java
+[extractive_summary_action_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/ExtractiveSummarization.java
+[multi_label_classification_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/MultiLabelClassifyDocument.java
+[multiple_actions_analysis_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/AnalyzeActions.java
 [recognize_entities_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/RecognizeEntitiesBatchDocuments.java
 [recognize_pii_entities_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/RecognizePiiEntitiesBatchDocuments.java
 [recognize_linked_entities_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/RecognizeLinkedEntitiesBatchDocuments.java
-[abstractive_summary_action_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/AbstractiveSummarization.java
-[extractive_summary_action_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/ExtractiveSummarization.java
-[dynamic_classification_sample]:  https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/DynamicClassifyBatchDocuments.java
+[recognize_healthcare_entities_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/AnalyzeHealthcareEntities.java
+[recognize_custom_entities_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/RecognizeCustomEntities.java
+[single_label_classification_sample]: https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/SingleLabelClassifyDocument.java
 
 ![Impressions](https://azure-sdk-impressions.azurewebsites.net/api/impressions/azure-sdk-for-java%2Fsdk%2Ftextanalytics%2Fazure-ai-textanalytics%2FREADME.png)