ComprehendConnector

Categories

Web

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Accesses the Amazon AI Comprehend Service for natural language processing on text.

Jump to Configuration

Typical Uses

  • Submitting text to the Amazon AWS Comprehend service for analysis to:
    • Detect dominant language
    • Determine sentiment information
    • Detect key phrases
    • Detect entities

How does it work?

The ComprehendConnector uses your Amazon AWS account credentials (either via a previously defined FME web connection, or by setting up a new FME web connection right from the transformer) to access the natural language processing service.

It will submit text to the service, and return features with attributes about that text. Each input text feature may result in several output features.

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.
  • All confidence scores are returned between 0 and 1. For more information about accuracy, see the Amazon Comprehend FAQs: https://aws.amazon.com/comprehend/faqs/

Configuration

Input Ports

This transformer accepts any feature.

Output Ports

Output will depend on the analysis chosen.

Language Detection

Detects the dominant language for text. The service may return multiple language guesses for an individual request.

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.

Sentiment Detection

Detects the sentiment for text.

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.

Key Phrase Detection

Detects the key phrases in text.

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.

Entity Detection

Detects the entities in text. The service can return multiple entities in a given text.

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.

The incoming feature is output through this port.

Features that cause the operation to fail are output through this port. An fme_rejection_code attribute, having the value ERROR_DURING_PROCESSING, will be added, along with a more descriptive fme_rejection_message attribute which contains more specific details as to the reason for the failure.

Note  If a feature comes in to the ComprehendConnector already having a value for fme_rejection_code, this value will be removed.

Rejected Feature Handling: can be set to either terminate the translation or continue running when it encounters a rejected feature. This setting is available both as a default FME option and as a workspace parameter.

Parameters

Credential Source

The ComprehendConnector can use credentials from different sources. Using a web connection integrates best with FME, but in some cases, you may wish to use one of the other sources.

Account

Available when the credential source is Web Connection. To create a Comprehend connection, click the 'Account' drop-down box and select 'Add Web Connection...'.

The connection can then be managed via Tools -> FME Options... -> Web Connections.

Region

The AWS Region through which to access Comprehend. To optimize latency, it is best practice to specify the correct region.

Access Key and Secret Access Key

Available when the credential source is Embedded. An access key ID and secret access key can be specified directly in the transformer instead of in a web connection.

Text

The text to be analyzed under the specified request action.

Action

The type of operation to perform. Choices are:

Language Detection

Detects language(s) for the text.

Key Phrase Detection

Detects key phrase(s) in the text.

Entity Detection

Detects entities in the text.

Sentiment Detection

Detects sentiments in the text.

Language

This parameter is available when the Action parameter is Entity Detection, Key Phrase Detection, or Sentiment Detection. This parameter specifies the language of the text. All text must be in the same language per transformer. If using an attribute value, it must be the language code (for example, “en”).

Reference for supported languages: https://docs.aws.amazon.com/comprehend/latest/dg/supported-languages.html

Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

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. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

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.

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

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.

Reference

Processing Behavior

Feature-Based

Feature Holding

No
Dependencies Amazon AWS Account with Comprehend access
Aliases AmazonAWSComprehendConnector
History Released FME 2019.2

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