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
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2. Setup and Requirements
Self-paced environment setup
- 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.
- 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
- 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.
- 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`
- 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].
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
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
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.
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.