Text Analytics API (v3.2-preview.1)
The Text Analytics API is a suite of natural language processing (NLP) services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. Functionality for analysis of text specific to the healthcare domain and personal information are also available in the API. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview
Sentiment
The API returns a detailed sentiment analysis for the input text. The analysis is done in multiple levels of granularity, start from the a document level, down to sentence and key terms (targets and assessments).
Select the testing console in the region where you created your resource:
West US West US 2 East US East US 2 West Central US South Central US West Europe North Europe Southeast Asia East Asia Australia East Brazil South Canada Central UK South Japan East Central US France Central Korea Central Japan West North Central US South Africa North UAE North Switzerland North Switzerland West Central India West US 3 Norway East Jio India WestRequest URL
Request parameters
(Optional) This value indicates which model will be used for scoring. If a model-version is not specified, the API should default to the latest, non-preview version.
(Optional) if set to true, response will contain request and document level statistics.
(Optional) If set to true, you opt-out of having your text input logged for troubleshooting. By default, Text Analytics logs your input text for 48 hours, solely to allow for troubleshooting issues in providing you with the Text Analytics natural language processing functions. Setting this parameter to true, disables input logging and may limit our ability to remediate issues that occur. Please see Cognitive Services Compliance and Privacy notes at https://aka.ms/cs-compliance for additional details, and Microsoft Responsible AI principles at https://www.microsoft.com/en-us/ai/responsible-ai.
(Optional) if set to true, response will contain not only sentiment prediction but also opinion mining (aspect-based sentiment analysis) results.
(Optional) Specifies the method used to interpret string offsets. Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information see https://aka.ms/text-analytics-offsets
Request headers
Request body
Collection of documents to analyze.
{
"documents": [
{
"id": "1",
"language": "en",
"text": "Great atmosphere. Close to plenty of restaurants, hotels, and transit! Staff are friendly and helpful."
}
]
}
{
"type": "object",
"required": [
"documents"
],
"properties": {
"documents": {
"type": "array",
"description": "The set of documents to process as part of this batch.",
"items": {
"type": "object",
"required": [
"id",
"text"
],
"properties": {
"id": {
"type": "string",
"description": "A unique, non-empty document identifier."
},
"text": {
"type": "string",
"description": "The input text to process."
},
"language": {
"type": "string",
"description": "(Optional) This is the 2 letter ISO 639-1 representation of a language. For example, use \"en\" for English; \"es\" for Spanish etc. If not set, use \"en\" for English as default."
}
},
"description": "Contains an input document to be analyzed by the service."
}
}
},
"description": "Contains a set of input documents to be analyzed by the service."
}
{
"documents": [
{
"id": "1",
"language": "en",
"text": "Great atmosphere. Close to plenty of restaurants, hotels, and transit! Staff are friendly and helpful."
}
]
}
{
"type": "object",
"required": [
"documents"
],
"properties": {
"documents": {
"type": "array",
"description": "The set of documents to process as part of this batch.",
"items": {
"type": "object",
"required": [
"id",
"text"
],
"properties": {
"id": {
"type": "string",
"description": "A unique, non-empty document identifier."
},
"text": {
"type": "string",
"description": "The input text to process."
},
"language": {
"type": "string",
"description": "(Optional) This is the 2 letter ISO 639-1 representation of a language. For example, use \"en\" for English; \"es\" for Spanish etc. If not set, use \"en\" for English as default."
}
},
"description": "Contains an input document to be analyzed by the service."
}
}
},
"description": "Contains a set of input documents to be analyzed by the service."
}
Response 200
A successful call results in a document sentiment prediction, as well as sentiment scores for each sentiment class (Positive, Negative, and Neutral)
{
"documents": [
{
"confidenceScores": {
"negative": 0,
"neutral": 0,
"positive": 1
},
"id": "1",
"sentences": [
{
"targets": [
{
"confidenceScores": {
"negative": 0,
"positive": 1
},
"length": 10,
"offset": 6,
"relations": [
{
"ref": "#/documents/0/sentences/0/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "atmosphere"
}
],
"confidenceScores": {
"negative": 0,
"neutral": 0,
"positive": 1
},
"length": 17,
"offset": 0,
"assessments": [
{
"confidenceScores": {
"negative": 0,
"positive": 1
},
"isNegated": false,
"length": 5,
"offset": 0,
"sentiment": "positive",
"text": "great"
}
],
"sentiment": "positive",
"text": "Great atmosphere."
},
{
"targets": [
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"length": 11,
"offset": 37,
"relations": [
{
"ref": "#/documents/0/sentences/1/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "restaurants"
},
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"length": 6,
"offset": 50,
"relations": [
{
"ref": "#/documents/0/sentences/1/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "hotels"
}
],
"confidenceScores": {
"negative": 0.01,
"neutral": 0.86,
"positive": 0.13
},
"length": 52,
"offset": 18,
"assessments": [
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"isNegated": false,
"length": 15,
"offset": 18,
"sentiment": "positive",
"text": "Close to plenty"
}
],
"sentiment": "neutral",
"text": "Close to plenty of restaurants, hotels, and transit!"
}
],
"sentiment": "positive",
"warnings": []
}
],
"errors": [],
"modelVersion": "2020-04-01"
}
{
"documents": [
{
"confidenceScores": {
"negative": 0,
"neutral": 0,
"positive": 1
},
"id": "1",
"sentences": [
{
"targets": [
{
"confidenceScores": {
"negative": 0,
"positive": 1
},
"length": 10,
"offset": 6,
"relations": [
{
"ref": "#/documents/0/sentences/0/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "atmosphere"
}
],
"confidenceScores": {
"negative": 0,
"neutral": 0,
"positive": 1
},
"length": 17,
"offset": 0,
"assessments": [
{
"confidenceScores": {
"negative": 0,
"positive": 1
},
"isNegated": false,
"length": 5,
"offset": 0,
"sentiment": "positive",
"text": "great"
}
],
"sentiment": "positive",
"text": "Great atmosphere."
},
{
"targets": [
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"length": 11,
"offset": 37,
"relations": [
{
"ref": "#/documents/0/sentences/1/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "restaurants"
},
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"length": 6,
"offset": 50,
"relations": [
{
"ref": "#/documents/0/sentences/1/assessments/0",
"relationType": "assessment"
}
],
"sentiment": "positive",
"text": "hotels"
}
],
"confidenceScores": {
"negative": 0.01,
"neutral": 0.86,
"positive": 0.13
},
"length": 52,
"offset": 18,
"assessments": [
{
"confidenceScores": {
"negative": 0.01,
"positive": 0.99
},
"isNegated": false,
"length": 15,
"offset": 18,
"sentiment": "positive",
"text": "Close to plenty"
}
],
"sentiment": "neutral",
"text": "Close to plenty of restaurants, hotels, and transit!"
}
],
"sentiment": "positive",
"warnings": []
}
],
"errors": [],
"modelVersion": "2020-04-01"
}
Response 400
Bad Request.
{
"error": {
"code": "InvalidRequest",
"message": "Invalid Request.",
"innererror": {
"code": "MissingInputRecords",
"message": "Missing input records."
}
}
}
{
"error": {
"code": "InvalidRequest",
"message": "Invalid Request.",
"innererror": {
"code": "MissingInputRecords",
"message": "Missing input records."
}
}
}
Response 500
Unexpected error
{
"error": {
"code": "InternalServerError",
"message": "Processing failed unexpectedly. Please try again later."
}
}
{
"error": {
"code": "InternalServerError",
"message": "Processing failed unexpectedly. Please try again later."
}
}
Code samples
@ECHO OFF
curl -v -X POST "https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment?model-version={string}&showStats={boolean}&loggingOptOut={boolean}&opinionMining={boolean}&stringIndexType=TextElement_v8"
-H "Content-Type: application/json"
-H "Ocp-Apim-Subscription-Key: {subscription key}"
--data-ascii "{body}"
using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;
namespace CSHttpClientSample
{
static class Program
{
static void Main()
{
MakeRequest();
Console.WriteLine("Hit ENTER to exit...");
Console.ReadLine();
}
static async void MakeRequest()
{
var client = new HttpClient();
var queryString = HttpUtility.ParseQueryString(string.Empty);
// Request headers
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");
// Request parameters
queryString["model-version"] = "{string}";
queryString["showStats"] = "{boolean}";
queryString["loggingOptOut"] = "{boolean}";
queryString["opinionMining"] = "{boolean}";
queryString["stringIndexType"] = "TextElement_v8";
var uri = "https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment?" + queryString;
HttpResponseMessage response;
// Request body
byte[] byteData = Encoding.UTF8.GetBytes("{body}");
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
response = await client.PostAsync(uri, content);
}
}
}
}
// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
public class JavaSample
{
public static void main(String[] args)
{
HttpClient httpclient = HttpClients.createDefault();
try
{
URIBuilder builder = new URIBuilder("https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment");
builder.setParameter("model-version", "{string}");
builder.setParameter("showStats", "{boolean}");
builder.setParameter("loggingOptOut", "{boolean}");
builder.setParameter("opinionMining", "{boolean}");
builder.setParameter("stringIndexType", "TextElement_v8");
URI uri = builder.build();
HttpPost request = new HttpPost(uri);
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");
// Request body
StringEntity reqEntity = new StringEntity("{body}");
request.setEntity(reqEntity);
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
if (entity != null)
{
System.out.println(EntityUtils.toString(entity));
}
}
catch (Exception e)
{
System.out.println(e.getMessage());
}
}
}
<!DOCTYPE html>
<html>
<head>
<title>JSSample</title>
<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>
<script type="text/javascript">
$(function() {
var params = {
// Request parameters
"model-version": "{string}",
"showStats": "{boolean}",
"loggingOptOut": "{boolean}",
"opinionMining": "{boolean}",
"stringIndexType": "TextElement_v8",
};
$.ajax({
url: "https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment?" + $.param(params),
beforeSend: function(xhrObj){
// Request headers
xhrObj.setRequestHeader("Content-Type","application/json");
xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
},
type: "POST",
// Request body
data: "{body}",
})
.done(function(data) {
alert("success");
})
.fail(function() {
alert("error");
});
});
</script>
</body>
</html>
#import <Foundation/Foundation.h>
int main(int argc, const char * argv[])
{
NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
NSString* path = @"https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment";
NSArray* array = @[
// Request parameters
@"entities=true",
@"model-version={string}",
@"showStats={boolean}",
@"loggingOptOut={boolean}",
@"opinionMining={boolean}",
@"stringIndexType=TextElement_v8",
];
NSString* string = [array componentsJoinedByString:@"&"];
path = [path stringByAppendingFormat:@"?%@", string];
NSLog(@"%@", path);
NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
[_request setHTTPMethod:@"POST"];
// Request headers
[_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
[_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
// Request body
[_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
NSURLResponse *response = nil;
NSError *error = nil;
NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];
if (nil != error)
{
NSLog(@"Error: %@", error);
}
else
{
NSError* error = nil;
NSMutableDictionary* json = nil;
NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
NSLog(@"%@", dataString);
if (nil != _connectionData)
{
json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
}
if (error || !json)
{
NSLog(@"Could not parse loaded json with error:%@", error);
}
NSLog(@"%@", json);
_connectionData = nil;
}
[pool drain];
return 0;
}
<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';
$request = new Http_Request2('https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment');
$url = $request->getUrl();
$headers = array(
// Request headers
'Content-Type' => 'application/json',
'Ocp-Apim-Subscription-Key' => '{subscription key}',
);
$request->setHeader($headers);
$parameters = array(
// Request parameters
'model-version' => '{string}',
'showStats' => '{boolean}',
'loggingOptOut' => '{boolean}',
'opinionMining' => '{boolean}',
'stringIndexType' => 'TextElement_v8',
);
$url->setQueryVariables($parameters);
$request->setMethod(HTTP_Request2::METHOD_POST);
// Request body
$request->setBody("{body}");
try
{
$response = $request->send();
echo $response->getBody();
}
catch (HttpException $ex)
{
echo $ex;
}
?>
########### Python 2.7 #############
import httplib, urllib, base64
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.urlencode({
# Request parameters
'model-version': '{string}',
'showStats': '{boolean}',
'loggingOptOut': '{boolean}',
'opinionMining': '{boolean}',
'stringIndexType': 'TextElement_v8',
})
try:
conn = httplib.HTTPSConnection('japanwest.api.cognitive.microsoft.com')
conn.request("POST", "/text/analytics/v3.2-preview.1/sentiment?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################
########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.parse.urlencode({
# Request parameters
'model-version': '{string}',
'showStats': '{boolean}',
'loggingOptOut': '{boolean}',
'opinionMining': '{boolean}',
'stringIndexType': 'TextElement_v8',
})
try:
conn = http.client.HTTPSConnection('japanwest.api.cognitive.microsoft.com')
conn.request("POST", "/text/analytics/v3.2-preview.1/sentiment?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################
require 'net/http'
uri = URI('https://japanwest.api.cognitive.microsoft.com/text/analytics/v3.2-preview.1/sentiment')
uri.query = URI.encode_www_form({
# Request parameters
'model-version' => '{string}',
'showStats' => '{boolean}',
'loggingOptOut' => '{boolean}',
'opinionMining' => '{boolean}',
'stringIndexType' => 'TextElement_v8'
})
request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"
response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
http.request(request)
end
puts response.body