ComprehendConnector

Connects to Amazon AI Comprehend for natural language processing on text.

Typical Uses

Detecting entities, phrases, language or sentiment.

How does it work?

The ComprehendConnector uses your Amazon AWS account credentials to access the natural language processing service.

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:

Detection Type	Analysis
Entity Detection	Detects linked or categorized entities.
Key Phrase Detection	Extracts key phrases.
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.

Usage Notes

For better performance, requests to the Comprehend service are made in parallel, and are returned as soon as they complete. Consequently, detection results will not be returned in the same order as their associated requests.

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
Entity Detection	Input feature(s), one copy for each entity identified, with details about the entity.	New feature(s), one for each entity identified, with details about the entity .
Key Phrase Detection	Input feature with identified key phrases in a list attribute.	New feature with identified key phrases in a list attribute.
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 sentiment and confidence details.	New feature with sentiment and confidence details.

Parameters

Authentication

Credential Source

Select the type of credentials to use:

Web Connection (Recommended): Use an Amazon Web Services web connection.
Embedded: Embed an access key ID and secret access key as parameters in the transformer.
System: Use credentials already configured on the system. This allows for using IAM role-based authentication. For more information about configuring AWS credentials system-wide, see Getting started with the AWS CLI.

Account

When Credential Source is Web Connection, select or create a Web Connection connecting to an Amazon Web ServicesWeb Service.

See Using Web Connections.

Region

Select the AWS Region through which to access Comprehend.

To optimize latency, it is best practice to specify the correct region.

Embedded Credentials

When Credential Source is Embedded:

Access Key ID	Provide S3 account credentials.
Secret Access Key	Provide S3 account credentials.

Request

Text

Provide the text to submit for analysis.

Action

Select an analysis type. Choices include:

Entity Detection
Key Phrase Detection
Language Detection
Sentiment Detection

Action > Entity Detection

Entity Detection Options

Language

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

If providing a value, use the language code, as in en for English, or Unknown [unk] for automatic language detection.

See Languages supported in Amazon Comprehend.

Added Attributes

Output features will receive these attributes.

_entities{}.text	The entity from the text.
_entities{}.confidence	A number between 0 and 1 that indicates the confidence score for the entity.
_entities{}.begin_offset	The entity beginning offset in the text.
_entities{}.end_offset	The entity ending offset in the text.
_entities{}.type	The type of the detected entity. Types can be found here: https://docs.aws.amazon.com/comprehend/latest/dg/how-entities.html
_text	The text analyzed.

Action > Key Phrase Detection

Key Phrase Detection Options

Language

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

If providing a value, use the language code, as in en for English, or Unknown [unk] for automatic language detection.

See Languages supported in Amazon Comprehend.

Added Attributes

Output features will receive these attributes.

_key_phrases{}.text	The key phrases from the text.
_key_phrases{}.confidence	A number between 0 and 1 that indicates the confidence score for the key phrase.
_key_phrases{}.begin_offset	The key phrase beginning offset in the text.
_key_phrases{}.end_offset	The key phrase ending offset in the text.
_text	The text analyzed.

Action > Language Detection

Language Detection Options

Language detection has no parameters to configure.

Added Attributes

Output features will receive these attributes.

_language_code	The language code guessed for the text. A list of available languages is available at: https://docs.aws.amazon.com/comprehend/latest/dg/supported-languages.html
_confidence	The probability that a given prediction is correct.
_text	The text analyzed.

Action > Sentiment Detection

Sentiment Detection Options

Language

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

If providing a value, use the language code, as in en for English, or Unknown [unk] for automatic language detection.

See Languages supported in Amazon Comprehend.

Added Attributes

Output features will receive these attributes.

_sentiment	The sentiment for the text. Possible values are: POSITIVE NEGATIVE NEUTRAL MIXED
_sentiment_postive	The confidence score for positive sentiment.
_sentiment_negative	The confidence score for negative sentiment.
_sentiment_neutral	The confidence score for neutral sentiment.
_sentiment_mixed	The confidence score for mixed sentiment.
_text	The text analyzed.

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	Amazon AWS Account with Comprehend access
Aliases	AmazonAWSComprehendConnector
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 ComprehendConnector 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.