GoogleLanguageConnector

Connects to Google Cloud AI for natural language processing on text.

Typical Uses

Detecting language or sentiment.

How does it work?

The GoogleLanguageConnector uses your Google Cloud account credentials to access Google’s Natural Language and Cloud Translation services.

Text is submitted to the service, and one or more features are output with attributes added according to the requested Detection Type.

Available services are:

Type	Analysis
Language Detection	Detects the dominant language.
Sentiment Detection	Detects text sentiment.

Optional Input Port

This transformer has two modes, depending on whether a connector is attached to the Input port or not:

Input-driven: When input features are connected, the transformer runs once for each feature it receives in the Input port.
Run Once: When no input features are connected, the transformer runs one time.

When the Input port is in use, the Initiator output port is also enabled.

Configuration

Input Ports

Output Ports

Output

Features with added attributes, as specified in parameters and according to Detection Type.

Detection Type	Output - Input-Driven	Output - Run Once
Language Detection	Input feature(s), one copy for each language identified, with details about the language.	New feature(s), one copy for each language identified, with details about the language.
Sentiment Detection	Input feature with a sentiment score.	New feature with a sentiment score.

Detection Type

Output - Input-Driven

Output - Run Once

Language Detection

Input feature(s), one copy for each language identified, with details about the language.

New feature(s), one copy for each language identified, with details about the language.

Sentiment Detection

Input feature with a sentiment score.

New feature with a sentiment score.

Parameters

Authentication

Credential Source

Select the type of credentials to use:

Web Connection (Recommended): Use a Google AI OAuth (recommended)or Google AI JSON Key web connection.
Application Default Credentials: Authenticate based on the system environment. This will attempt to resolve credentials using the following sources, in order:
- The credential file pointed to by the environment variable GOOGLE_APPLICATION_CREDENTIALS
- The credential file created by using the Google Cloud CLI
- The metadata server on a Google Cloud Engine Virtual Machine instance.
  See Google Cloud SDK > Authentication > How Application Default Credentials works.

Account

When Credential Source is Web Connection, select or create a Web Connection connecting to a Google AI OAuth or Google AI JSON Key Web Service.

See Using Web Connections.

Detection Type > Language Detection

Language Detection Options

Language detection has no parameters to configure.

Added Attributes

Output features will receive these attributes.

_language_code

A detected language’s code.

If the language cannot be detected, und (undetermined) will be returned. See Google Cloud Language support.

_confidence

The confidence in language detection, a value between 0 and 1.

_original_text

The submitted text.

Detection Type > Sentiment Detection

Sentiment Detection Options

Language

Select or provide the language of the Text. All text must be in the same language per transformer.

The default, Detect Language, will perform automatic detection.

If providing a value, use the language code, as in en for English.

See Google Cloud Language support.

Added Attributes

Output features will receive these attributes.

_sentiment_score

The sentiment score ranges between -1.0 (negative) and 1.0 (positive) and corresponds to the overall emotional leaning of the text.

See Natural Language AI.

_original_text

The submitted text.

Editing Transformer Parameters

Transformer parameters can be set by directly entering values, using expressions, or referencing other elements in the workspace such as attribute values or user parameters. Various editors and context menus are available to assist. To see what is available, click beside the applicable parameter.

How to Set Parameter Values

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters.

Using the Text Editor

The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.

Text Editor

Using the Arithmetic Editor

The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.

Arithmetic Editor

Conditional Values

Set values depending on one or more test conditions that either pass or fail.

Parameter Condition Definition Dialog

Content

Expressions and strings can include a number of functions, characters, parameters, and more.

When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.

Content Types

String Functions	These functions manipulate and format strings.
Special Characters	A set of control characters is available in the Text Editor.
Math Functions	Math functions are available in both editors.
Date/Time Functions	Date and time functions are available in the Text Editor.
Math Operators	These operators are available in the Arithmetic Editor.
FME Feature Functions	These return primarily feature-specific values.
FME Parameters	FME and workspace-specific parameters may be used.
Creating and Modifying User Parameters	Create your own editable parameters.

Dialog Options - Tables

Table Tools

Transformers with table-style parameters have additional tools for populating and manipulating values.

Row Reordering

Enabled once you have clicked on a row item. Choices include:

Add a row
Remove a row
Move current row up one
Move current row down one
Move current row to top
Move current row to bottom

Cut, Copy, and Paste

Enabled once you have clicked on a row item. Choices include:

Cut a row - delete and copy to clipboard
Copy a row to the clipboard
Paste a row from the clipboard

Cut, copy, and paste may be used within a transformer, or between transformers.

Filter

Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output.

Import

Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.

Reset/Refresh

Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers.

Note: Not all tools are available in all transformers.

For more information, see Transformer Parameter Menu Options.

Reference

Processing Behavior	Feature-Based
Feature Holding	No
Dependencies	Google Cloud Account with access to the Cloud Natural Language and Cloud Translation APIs
Aliases
History	Released FME 2019.2

FME Online Resources

The FME Community and Support Center Knowledge Base have a wealth of information, including active forums with 35,000+ members and thousands of articles.

Search for all results about the GoogleLanguageConnector on the FME Community.

Examples may contain information licensed under the Open Government Licence – Vancouver, Open Government Licence - British Columbia, and/or Open Government Licence – Canada.