Bidding and award information extraction - Basic Edition service

This model is the Basic Edition and supports parsing for 13 fields. If you need the Premium Edition, which supports separate parsing for bidding and award information, more fields, and higher accuracy, see Bidding and award information extraction - Premium Edition service.

Service activation and resource plan purchase

Before you start, ensure that the service is activated. After activation, you can purchase a resource plan.

• Activate service: Activation link

• Purchase resource plan: Purchase link

Service invocation and debugging

For more information, see Model invocation.

For SDK examples, see SDK examples.

Debug

Configure access credentials using environment variables

1. Notes:

   1. An AccessKey for an Alibaba Cloud account has full access permissions to all APIs, which poses a high security threat. We strongly recommend that you create and use a Resource Access Management (RAM) user for API access or daily operations and maintenance (O&M). To create a RAM user, log on to the RAM console.

   2. To prevent key leakage, do not hardcode your AccessKey ID and AccessKey secret in your code. Instead, configure them as environment variables.

2. Configure on Linux and macOS

   export NLP_AK_ENV=<access_key_id>
   export NLP_SK_ENV=<access_key_secret>

   Replace <access_key_id> with your AccessKey ID and <access_key_secret> with your AccessKey secret. For more information, see Step 2: Obtain an AccessKey for your account.

3. Configure on Windows

   1. Create an environment variable file. Add the NLP_AK_ENV and NLP_SK_ENV environment variables and set them to your AccessKey ID and AccessKey secret.

   2. Restart Windows.

Java code example

/**
 * An AccessKey of an Alibaba Cloud account has full access permissions to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user for API access or daily O&M. To create a RAM user, log on to the RAM console.
 * This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
 * To prevent key leakage, do not hardcode the AccessKey ID and AccessKey secret in your code. This is strongly recommended.
 */
String accessKeyId = System.getenv("NLP_AK_ENV");
String accessKeySecret = System.getenv("NLP_SK_ENV");
DefaultProfile defaultProfile = DefaultProfile.getProfile("cn-hangzhou",accessKeyId,accessKeySecret);
IAcsClient client = new DefaultAcsClient(defaultProfile);
String content = "Bidding document text";
RunPreTrainServiceRequest request = new RunPreTrainServiceRequest();
request.setServiceName("NLP-NER-ZhaoBiao-AutoML");
request.setPredictContent(content);
RunPreTrainServiceResponse response = client.getAcsResponse(request);
System.out.println(response.getPredictResult());

Python code example

# Install dependencies
pip install aliyun-python-sdk-core
pip install aliyun-python-sdk-nlp-automl

# -*- coding: utf-8 -*-
import json
import os

from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.acs_exception.exceptions import ClientException
from aliyunsdkcore.acs_exception.exceptions import ServerException
from aliyunsdknlp_automl.request.v20191111 import RunPreTrainServiceRequest

"""
 * An AccessKey of an Alibaba Cloud account has full access permissions to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user for API access or daily O&M. To create a RAM user, log on to the RAM console.
 * This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
 * To prevent key leakage, do not hardcode the AccessKey ID and AccessKey secret in your code. This is strongly recommended.
"""
access_key_id = os.environ['NLP_AK_ENV']
access_key_secret = os.environ['NLP_SK_ENV']

# Initialize the AcsClient instance
client = AcsClient(
  access_key_id,
  access_key_secret,
  "cn-hangzhou"
);

content = 'Bidding document text'

# Initialize a request and set its parameters
request = RunPreTrainServiceRequest.RunPreTrainServiceRequest()
request.set_ServiceName('NLP-NER-ZhaoBiao-AutoML')
request.set_PredictContent(content)

# Print the response
response = client.do_action_with_exception(request)
resp_obj = json.loads(response)
predict_result = json.loads(resp_obj['PredictResult'])
print(predict_result['ner_dic'])

Extracted fields and descriptions