TextAnalyticsClient Class
Definition
Important
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The client to use for interacting with the Azure Cognitive Service for Language, which includes Text Analytics.
public class TextAnalyticsClient
type TextAnalyticsClient = class
Public Class TextAnalyticsClient
- Inheritance
-
TextAnalyticsClient
Constructors
TextAnalyticsClient() |
Protected constructor to allow mocking. |
TextAnalyticsClient(Uri, AzureKeyCredential, TextAnalyticsClientOptions) |
Initializes a new instance of the AzureKeyCredential class for the specified service instance. |
TextAnalyticsClient(Uri, AzureKeyCredential) |
Initializes a new instance of the AzureKeyCredential class for the specified service instance. |
TextAnalyticsClient(Uri, TokenCredential, TextAnalyticsClientOptions) |
Initializes a new instance of the TextAnalyticsClient class for the specified service instance. |
TextAnalyticsClient(Uri, TokenCredential) |
Initializes a new instance of the TextAnalyticsClient class for the specified service instance. |
Methods
AbstractiveSummarize(WaitUntil, IEnumerable<String>, String, AbstractiveSummarizeOptions, CancellationToken) |
Performs abstractive summarization on a given set of documents, which consists of generating a summary with concise, coherent sentences or words which are not simply extract sentences from the original document. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AbstractiveSummarize(WaitUntil, IEnumerable<TextDocumentInput>, AbstractiveSummarizeOptions, CancellationToken) |
Performs abstractive summarization on a given set of documents, which consists of generating a summary with concise, coherent sentences or words which are not simply extract sentences from the original document. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AbstractiveSummarizeAsync(WaitUntil, IEnumerable<String>, String, AbstractiveSummarizeOptions, CancellationToken) |
Performs abstractive summarization on a given set of documents, which consists of generating a summary with concise, coherent sentences or words which are not simply extract sentences from the original document. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AbstractiveSummarizeAsync(WaitUntil, IEnumerable<TextDocumentInput>, AbstractiveSummarizeOptions, CancellationToken) |
Performs abstractive summarization on a given set of documents, which consists of generating a summary with concise, coherent sentences or words which are not simply extract sentences from the original document. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeActions(WaitUntil, IEnumerable<String>, TextAnalyticsActions, String, AnalyzeActionsOptions, CancellationToken) |
Performs one or more text analysis actions on a set of documents. The list of supported actions includes:
For document length limits, maximum batch size, and supported text encoding, see here. |
AnalyzeActions(WaitUntil, IEnumerable<TextDocumentInput>, TextAnalyticsActions, AnalyzeActionsOptions, CancellationToken) |
Performs one or more text analysis actions on a set of documents. The list of supported actions includes:
For document length limits, maximum batch size, and supported text encoding, see here. |
AnalyzeActionsAsync(WaitUntil, IEnumerable<String>, TextAnalyticsActions, String, AnalyzeActionsOptions, CancellationToken) |
Performs one or more text analysis actions on a set of documents. The list of supported actions includes:
For document length limits, maximum batch size, and supported text encoding, see more information here. |
AnalyzeActionsAsync(WaitUntil, IEnumerable<TextDocumentInput>, TextAnalyticsActions, AnalyzeActionsOptions, CancellationToken) |
Performs one or more text analysis actions on a set of documents. The list of supported actions includes:
For document length limits, maximum batch size, and supported text encoding, see here. |
AnalyzeHealthcareEntities(WaitUntil, IEnumerable<String>, String, AnalyzeHealthcareEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of healthcare entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeHealthcareEntities(WaitUntil, IEnumerable<TextDocumentInput>, AnalyzeHealthcareEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of healthcare entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeHealthcareEntitiesAsync(WaitUntil, IEnumerable<String>, String, AnalyzeHealthcareEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of healthcare entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeHealthcareEntitiesAsync(WaitUntil, IEnumerable<TextDocumentInput>, AnalyzeHealthcareEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of healthcare entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentiment(String, String, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative or neutral sentiment contained in the document, as well as a score indicating the model's confidence in the predicted sentiment. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentimentAsync(String, String, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative, neutral or mixed sentiment contained in the document, as well as a score indicating the model's confidence in the predicted sentiment. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentimentBatch(IEnumerable<String>, String, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative or neutral sentiment contained in the documents, as well as scores indicating the model's confidence in each of the predicted sentiments. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentimentBatch(IEnumerable<TextDocumentInput>, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative or neutral sentiment contained in the documents, as well as scores indicating the model's confidence in each of the predicted sentiments. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentimentBatchAsync(IEnumerable<String>, String, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative or neutral sentiment contained in the documents, as well as scores indicating the model's confidence in each of the predicted sentiments. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
AnalyzeSentimentBatchAsync(IEnumerable<TextDocumentInput>, AnalyzeSentimentOptions, CancellationToken) |
Runs a predictive model to identify the positive, negative or neutral sentiment contained in the documents, as well as scores indicating the model's confidence in each of the predicted sentiments. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguage(String, String, CancellationToken) |
Runs a predictive model to determine the language the passed-in document is written in, and returns the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguageAsync(String, String, CancellationToken) |
Runs a predictive model to determine the language the passed-in document is written in, and returns the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguageBatch(IEnumerable<DetectLanguageInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to determine the language the passed-in documents are written in, and returns, for each one, the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguageBatch(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to determine the language the passed-in documents are written in, and returns, for each one, the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguageBatchAsync(IEnumerable<DetectLanguageInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to determine the language the passed-in documents are written in, and returns, for each one, the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
DetectLanguageBatchAsync(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to determine the language the passed-in documents are written in, and returns, for each one, the detected language as well as a score indicating the model's confidence that the inferred language is correct. Scores close to 1 indicate high certainty in the result. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractiveSummarize(WaitUntil, IEnumerable<String>, String, ExtractiveSummarizeOptions, CancellationToken) |
Performs extractive summarization on the given documents, which consists of extracting sentences that collectively represent the most important or relevant information within the original content. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractiveSummarize(WaitUntil, IEnumerable<TextDocumentInput>, ExtractiveSummarizeOptions, CancellationToken) |
Performs extractive summarization on the given documents, which consists of extracting sentences that collectively represent the most important or relevant information within the original content. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractiveSummarizeAsync(WaitUntil, IEnumerable<String>, String, ExtractiveSummarizeOptions, CancellationToken) |
Performs extractive summarization on the given documents, which consists of extracting sentences that collectively represent the most important or relevant information within the original content. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractiveSummarizeAsync(WaitUntil, IEnumerable<TextDocumentInput>, ExtractiveSummarizeOptions, CancellationToken) |
Performs extractive summarization on the given documents, which consists of extracting sentences that collectively represent the most important or relevant information within the original content. For a list of languages supported by this operation, see https://learn.microsoft.com/azure/cognitive-services/language-service/summarization/language-support. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrases(String, String, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in document. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrasesAsync(String, String, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in document. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrasesBatch(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in documents. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrasesBatch(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in documents. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrasesBatchAsync(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in documents. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
ExtractKeyPhrasesBatchAsync(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a model to identify a collection of significant phrases found in the passed-in documents. For example, for the document "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
MultiLabelClassify(WaitUntil, IEnumerable<String>, String, String, String, MultiLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with multiple labels in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
MultiLabelClassify(WaitUntil, IEnumerable<TextDocumentInput>, String, String, MultiLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with multiple labels in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
MultiLabelClassifyAsync(WaitUntil, IEnumerable<String>, String, String, String, MultiLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with multiple labels in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
MultiLabelClassifyAsync(WaitUntil, IEnumerable<TextDocumentInput>, String, String, MultiLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with multiple labels in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeCustomEntities(WaitUntil, IEnumerable<String>, String, String, String, RecognizeCustomEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of custom named entities in the passed-in documents, and categorize those entities into custom types such as contracts or financial documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-named-entity-recognition/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeCustomEntities(WaitUntil, IEnumerable<TextDocumentInput>, String, String, RecognizeCustomEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of custom named entities in the passed-in documents, and categorize those entities into custom types such as contracts or financial documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-named-entity-recognition/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeCustomEntitiesAsync(WaitUntil, IEnumerable<String>, String, String, String, RecognizeCustomEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of custom named entities in the passed-in documents, and categorize those entities into custom types such as contracts or financial documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-named-entity-recognition/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeCustomEntitiesAsync(WaitUntil, IEnumerable<TextDocumentInput>, String, String, RecognizeCustomEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of custom named entities in the passed-in documents, and categorize those entities into custom types such as contracts or financial documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-named-entity-recognition/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntities(String, String, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in document, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntitiesAsync(String, String, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in document, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntitiesBatch(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in documents, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntitiesBatch(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in documents, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntitiesBatchAsync(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in documents, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeEntitiesBatchAsync(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of named entities in the passed-in documents, and categorize those entities into types such as person, location, or organization. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/concepts/named-entity-categories. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntities(String, String, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntitiesAsync(String, String, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in document, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntitiesBatch(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in documents, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntitiesBatch(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in documents, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntitiesBatchAsync(IEnumerable<String>, String, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in documents, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizeLinkedEntitiesBatchAsync(IEnumerable<TextDocumentInput>, TextAnalyticsRequestOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities found in the passed-in documents, and include information linking the entities to their corresponding entries in a well-known knowledge base. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntities(String, String, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntitiesAsync(String, String, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntitiesBatch(IEnumerable<String>, String, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntitiesBatch(IEnumerable<TextDocumentInput>, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntitiesBatchAsync(IEnumerable<String>, String, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
RecognizePiiEntitiesBatchAsync(IEnumerable<TextDocumentInput>, RecognizePiiEntitiesOptions, CancellationToken) |
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, drivers license number, or credit card number. For more information on available categories, see https://aka.ms/azsdk/language/pii. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
SingleLabelClassify(WaitUntil, IEnumerable<String>, String, String, String, SingleLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with a single label in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
SingleLabelClassify(WaitUntil, IEnumerable<TextDocumentInput>, String, String, SingleLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with a single label in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
SingleLabelClassifyAsync(WaitUntil, IEnumerable<String>, String, String, String, SingleLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with a single label in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
SingleLabelClassifyAsync(WaitUntil, IEnumerable<TextDocumentInput>, String, String, SingleLabelClassifyOptions, CancellationToken) |
Runs a predictive model to identify a classify each document with a single label in the passed-in documents. For more information on available categories, see https://docs.microsoft.com/azure/cognitive-services/language-service/custom-text-classification/overview. For a list of languages supported by this operation, see https://aka.ms/talangs. For document length limits, maximum batch size, and supported text encoding, see https://aka.ms/azsdk/textanalytics/data-limits. |
Applies to
Azure SDK for .NET