AzureTextAnalyticsConnector

Input

This transformer accepts any feature.

Output

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 (for example, en).
_language_name	The name of the language (for example, English).
_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

_sentiment_value

The sentiment indication. A value closer to 0 is negative, value near 0.5 is neutral and a value closer to 1 is positive.

_text

The text analyzed.

Key Phrases Detection

Detects the key phrases for text.

Attributes

_key_phrases{}	The important words/phrases in the text. Outputs as a list attribute.
_text	The text analyzed.

Entities Detection

Detects the entities of the text.

Attributes

_name	The name of the entity.
_type	The type of entity (for example, Person).
_sub_type	The sub type.
_wikipedia_id	The Wikipedia title for the entity.
_wikipedia_language	The iso language code of the Wikipedia article.
_wikipedia_url	The url to the Wikipedia page
_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.

Features can be rejected when the data limits for the Azure Text Analytics service are exceeded. A possible workaround is to reduce the size or number of characters in the request. The Decelerator transformer can be used to prevent the service's rate limit from being exceeded.

The list of data limits for the Azure Text Analytics service is found at: https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#data-limits

Note If a feature comes in to the AzureTextAnalyticsConnector 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.

Authentication

To use the AzureTextAnalyticsConnector or the AzureComputerVisionConnector you will need a Cognitive Services Account, then generate an endpoint and key to authenticate through our connectors.

Credential Source

The AzureTextAnalyticsConnector 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.

Web Connection - use an Azure Cognitive Services web connection stored in the FME web connections database
Embedded - embed an endpoint and secret key as parameters in the transformer

Account

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

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

Endpoint and Secret Key

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

Request

Text

The text to perform detection on.

Detection Type

The type of operation to perform. Choices are:

Entities Detection: Detects entities for the text.
Key Phrases Detection: Detects key phrases for the text.
Language Detection: Detects language(s) for the text.
Sentiment Detection: Detects sentiment for the text.

Parameters - Entities Detection

Detect Entities Options

Language

The language of the text. All text must be in the same language per transformer. The language code must be used for the attribute value (for example, “en”).

For more information on supported languages: https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/language-support

Parameters - Key Phrases Detection

Detect Key Phrases Options

Language

The language of the text. All text must be in the same language per transformer. The language code must be used for the attribute value (for example, “en”).

For more information on supported languages: https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/language-support

Parameters - Language Detection

Detect Language Options

Language detection does not require any additional parameters.

Parameters - Sentiment Detection

Detect Sentiment Options

Language

The language of the text. All text must be in the same language per transformer. The language code must be used for the attribute value (for example, “en”).

For more information on supported languages: https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/language-support

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.

Processing Behavior	Feature-Based
Feature Holding	No
Dependencies	Azure Cognitive Services Account
Aliases
History	Released FME 2019.2

AzureTextAnalyticsConnector

Typical Uses

How does it work?

Usage Notes

Configuration

Input Ports

Output Ports

Parameters

Editing Transformer Parameters

Reference

FME Community