Textrics API Stack

NER Analysis API Implementation

Extraction of named entities from unstructured contextual data such as names, locations, brands, etc. is helpful when it comes to analysis. With the help of our efficient Name Entity Recognition, extracting these entities from articles is faster.

Endpoint

https://api.textrics.ai/ner_analysis_api.php

We support POST method to communicate with API.

Parameters

1. user_text - This parameter is required
This is the text (sentence) which you wish to send to application to analyse.

2. api_key - This parameter is required
This is used to identify the user and the active subscription plan.

3. api_token - This parameter is required
This is used to authenticate the above user account.

API Script

<?php
if ($_SERVER["REQUEST_METHOD"] == "POST") {
    $text = trim($_POST['user_text']);			// input variable containing text //
    if($text!='' && is_numeric($text)!=1){
	$apiUrl = 'https://api.textrics.ai/ner_analysis_api.php';		// API URL //
    $args['user_text'] = $text;
	$args['api_key'] = 'A32NBK55K3'; 		// user specific key to validate the account //
	$args['api_token'] = 'P4lwpqT0YZYSVefSh44ADkvlJ8pesZDI';   // respective token to validate user credentials //

    $options=[
      CURLOPT_RETURNTRANSFER => true,
      CURLOPT_POSTFIELDS => $args,
      CURLOPT_CUSTOMREQUEST => "POST",
      CURLOPT_HTTPHEADER => ['Content-Type: multipart/form-data']
      ];
    $ch = curl_init($apiUrl);
    curl_setopt_array($ch, $options);
    $response1 = curl_exec($ch);
    echo $err = curl_error($ch); 
    curl_close($ch);	
    $response =  json_decode($response1,true);		// API output is stored in $response variable //
	}
	else
	{
        $message= 'Error: Input Text is incorrect.';
	}
}
?>

Sample of retrieving the output

<?php
if(!empty($response))
{
	echo "Input Text - ".$text;
	echo "<pre style='text-align:left;'>"; 
	print_r($response);		// Printing the $response output on page //
	echo "</pre>"; 
}
if(!empty($message))
{
	echo $message;
}
?>

Response Format

The response is structured in JSON as follows:

Array
(
    [response] => 1
    [data] => Array
        (
            [0] => Array
                (
                    [Module] => NER
                    [Prediction] => 
The train was cancelled. In spite of that, we arrived on time.
[]
                    [Confidence] => NA
                )
        )
    [message] => success
)

API Response Codes