Using the Natural Language API with C#

1. Overview

In this codelab you will focus on using the Natural Language API with C#. You will learn how to perform sentiment, entity and syntax analysis.

The Google Cloud Natural Language API provides natural language understanding technologies to developers, including sentiment analysis, entity analysis, and syntax analysis.

What you'll learn

• How to use the Cloud Shell
• How to Enable the Natural Language API
• How to Authenticate API requests
• How to install the Google Cloud client library for C#
• How to perform Sentiment Analysis
• How to perform Entity Analysis
• How to perform Syntax Analysis

What you'll need

• A Google Cloud Platform Project
• A Browser, such Chrome or Firefox
• Familiarity using C#

Survey

How will you use this tutorial?

Read it through only Read it and complete the exercises

How would you rate your experience with C#?

Novice Intermediate Proficient

How would you rate your experience with using Google Cloud Platform services?

Novice Intermediate Proficient

2. Setup and Requirements

Self-paced environment setup

1. Sign-in to the Google Cloud Console and create a new project or reuse an existing one. If you don't already have a Gmail or Google Workspace account, you must create one.

• The Project name is the display name for this project's participants. It is a character string not used by Google APIs. You can always update it.
• The Project ID is unique across all Google Cloud projects and is immutable (cannot be changed after it has been set). The Cloud Console auto-generates a unique string; usually you don't care what it is. In most codelabs, you'll need to reference your Project ID (typically identified as PROJECT_ID). If you don't like the generated ID, you might generate another random one. Alternatively, you can try your own, and see if it's available. It can't be changed after this step and remains for the duration of the project.
• For your information, there is a third value, a Project Number, which some APIs use. Learn more about all three of these values in the documentation.

Caution: A project ID is globally unique and can't be used by anyone else after you've selected it. You are the only user of that ID. Even if a project is deleted, the ID can't be used again

Note: If you use a Gmail account, you can leave the default location set to No organization. If you use a Google Workspace account, choose a location that makes sense for your organization.

2. Next, you'll need to enable billing in the Cloud Console to use Cloud resources/APIs. Running through this codelab won't cost much, if anything at all. To shut down resources to avoid incurring billing beyond this tutorial, you can delete the resources you created or delete the project. New Google Cloud users are eligible for the $300 USD Free Trial program.

Start Cloud Shell

While Google Cloud can be operated remotely from your laptop, in this codelab you will be using Google Cloud Shell, a command line environment running in the Cloud.

Activate Cloud Shell

1. From the Cloud Console, click Activate Cloud Shell .

If this is your first time starting Cloud Shell, you're presented with an intermediate screen describing what it is. If you were presented with an intermediate screen, click Continue.

It should only take a few moments to provision and connect to Cloud Shell.

This virtual machine is loaded with all the development tools needed. It offers a persistent 5 GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. Much, if not all, of your work in this codelab can be done with a browser.

Once connected to Cloud Shell, you should see that you are authenticated and that the project is set to your project ID.

2. Run the following command in Cloud Shell to confirm that you are authenticated:

gcloud auth list

Command output

 Credentialed Accounts
ACTIVE  ACCOUNT
*       <my_account>@<my_domain.com>

To set the active account, run:
    $ gcloud config set account `ACCOUNT`

Note: The gcloud command-line tool is the powerful and unified command-line tool in Google Cloud. It comes preinstalled in Cloud Shell. You will notice its support for tab completion. You may be prompted to authenticate the first time you run a command. For more information, see gcloud command-line tool overview.

3. Run the following command in Cloud Shell to confirm that the gcloud command knows about your project:

gcloud config list project

Command output

[core]
project = <PROJECT_ID>

If it is not, you can set it with this command:

gcloud config set project <PROJECT_ID>

Command output

Updated property [core/project].

Note: If you're completing this tutorial outside of Cloud Shell, follow Set up Application Default Credentials.

3. Enable the Natural Language API

Before you can begin using the Natural Language API you must enable the API. Using the Cloud Shell you can enable the API by using the following command:

gcloud services enable language.googleapis.com

Note: If this command ERRORs, check that the current Project ID matches your codelab Project ID.

Use the following command to find the current Project ID being used by Cloud Shell:

gcloud info | grep "project"

If the Project ID is not correct, use the following command to use the correct Project ID:

gcloud config set project <PROJECT_ID>

Replace <PROJECT_ID> with the correct Project ID.

4. Install the Google Cloud Natural Language API client library for C#

First, create a simple C# console application that you will use to run Natural Language API samples:

dotnet new console -n NaturalLanguageApiDemo

You should see the application created and dependencies resolved:

The template "Console Application" was created successfully.
Processing post-creation actions...
...
Restore succeeded.

Next, navigate to NaturalLanguageApiDemo folder:

cd NaturalLanguageApiDemo/

And add Google.Cloud.Language.V1 NuGet package to the project:

dotnet add package Google.Cloud.Language.V1

info : Adding PackageReference for package 'Google.Cloud.Language.V1' into project '/home/atameldev/NaturalLanguageApiDemo/NaturalLanguageApiDemo.csproj'.
log  : Restoring packages for /home/atameldev/NaturalLanguageApiDemo/NaturalLanguageApiDemo.csproj...
...
info : PackageReference for package 'Google.Cloud.Language.V1' version '1.1.0' added to file '/home/atameldev/NaturalLanguageApiDemo/NaturalLanguageApiDemo.csproj'.

Now, you're ready to use the Natural Language API!

5. Sentiment Analysis

In this section you will perform Sentiment Analysis on a string and find out the Score and Magnitude using the Natural Language API.

The Score of the sentiment ranges between -1.0 (negative) and 1.0 (positive) and corresponds to the overall sentiment from the given information.

The Magnitude of the sentiment ranges from 0.0 to +infinity and indicates the overall strength of sentiment from the given information. The more information that is provided the higher the magnitude.

Open the code editor from the top right side of the Cloud Shell:

Navigate to the Program.cs file inside the NaturalLanguageApiDemo folder and replace the code with the following:

using System;
using Google.Cloud.Language.V1;

namespace NaturalLanguageApiDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            var text = "Yukihiro Matsumoto is great!";
            var client = LanguageServiceClient.Create();
            var response = client.AnalyzeSentiment(Document.FromPlainText(text));
            var sentiment = response.DocumentSentiment;
            Console.WriteLine($"Score: {sentiment.Score}");
            Console.WriteLine($"Magnitude: {sentiment.Magnitude}");
        }
    }
}

Take a minute or two to study the code and see how the snippet of code is used to perform sentiment analysis on the string "Yukihiro Matsumoto is great!".

Back in Cloud Shell, run the app:

dotnet run

You should see the following output:

Score: 0.9
Magnitude: 0.9

Note: If this C# code does not work for you, verify the instructions you performed during Authenticate API requests step.

Using the following command to verify the value of GOOGLE_APPLICATION_CREDENTIALS environment variable:

echo GOOGLE_APPLICATION_CREDENTIALS

It should output the value "~/key.json".

If it does, next check that a service account was created and is located at "~/key.json" by using:

cat "~/key.json"

You should see something similar to:

{

"type": "service_account",

"project_id": "PROJECT_ID",

"private_key_id": "ff31939192529e07f42e4535fb20bb029def1276",

"Private_key":...

If you don't, revisit the Authenticate API requests step.

Summary

In this step, you were able to perform Sentiment Analysis on a string of text and print out the score and magnitude. Read more about Sentiment Analysis.

6. Entity Analysis

Entity analysis inspects the given information for entities by searching for proper nouns such as public figures, landmarks, etc., and returns information about those entities.

To perform Entity analysis, navigate to the Program.cs file inside the NaturalLanguageApiDemo folder and replace the code with the following:

using System;
using Google.Cloud.Language.V1;

namespace NaturalLanguageApiDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            var text = "Yukihiro Matsumoto is great!";
            var client = LanguageServiceClient.Create();
            var response = client.AnalyzeEntitySentiment(Document.FromPlainText(text));

            foreach (var entity in response.Entities)
            {
                Console.WriteLine($"Entity: \"{entity.Name}\" ({entity.Type})");
                if (entity.Metadata.ContainsKey("wikipedia_url"))
                {
                    Console.WriteLine($"URL: {entity.Metadata["wikipedia_url"]}");
                }
            }
        }
    }
}

Take a minute or two to study the code and see how the snippet of code is used to perform entity analysis on the string "Yukihiro Matsumoto is great!".

Back in Cloud Shell, run the app:

dotnet run

You should see the following output:

Entity: "Yukihiro Matsumoto" (Person)
URL: https://en.wikipedia.org/wiki/Yukihiro_Matsumoto

Summary

In this step, you were able to perform Entity Analysis on a string of text and printed its entities. Read more about Entity Analysis.

7. Syntax Analysis

Syntactic Analysis extracts linguistic information, breaking up the given text into a series of sentences and tokens (generally, word boundaries), providing further analysis on those tokens.

This example will print out the number of sentences, tokens, and provide the part of speech for each token.

To perform Syntax Analysis, navigate to the Program.cs file inside the NaturalLanguageApiDemo folder and replace the code with the following:

using System;
using Google.Cloud.Language.V1;
using static Google.Cloud.Language.V1.AnnotateTextRequest.Types;

namespace NaturalLanguageApiDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            var text = "Yukihiro Matsumoto is great!";
            var client = LanguageServiceClient.Create();
            var response = client.AnnotateText(Document.FromPlainText(text), 
                new Features { ExtractSyntax = true });

            var sentences = response.Sentences;
            var tokens = response.Tokens;

            Console.WriteLine($"Sentences: {sentences.Count}");
            Console.WriteLine($"Tokens: {tokens.Count}");

            foreach (var token in tokens)
            {
                Console.WriteLine($"{token.PartOfSpeech.Tag} {token.Text.Content}");
            }
        }
    }
}

Take a minute or two to study the code and see how the snippet of code is used to perform syntax analysis on the string "Yukihiro Matsumoto is great!".

Back in Cloud Shell, run the app:

dotnet run

You should see the following output:

Sentences: 1
Tokens: 5
Noun Yukihiro
Noun Matsumoto
Verb is
Adj great
Punct !

A visual interpretation is shown below.

Note: You can create your own parse trees with the Natural Language demo available here: https://cloud.google.com/natural-language/.

Summary

In this step, you were able to perform Syntax Analysis on a simple string of text and printed out the number of sentences, number of tokens, and linguistic information for each token. Read more about Syntax Analysis.

8. Congratulations!

You learned how to use the Natural Language API using C# to perform different kinds of analyses on information!

Clean up

To avoid incurring charges to your Google Cloud Platform account for the resources used in this quickstart:

• Go to the Cloud Platform Console.
• Select the project you want to shut down, then click ‘Delete' at the top: this schedules the project for deletion.

Learn More

• Google Cloud Natural Language API: https://cloud.google.com/natural-language/docs/
• C#/.NET on Google Cloud Platform: https://cloud.google.com/dotnet/
• Google Cloud .NET client: https://googlecloudplatform.github.io/google-cloud-dotnet/

License

This work is licensed under a Creative Commons Attribution 2.0 Generic License.