Extract Noun Phrases Using Term Extraction Transformation in SSIS

In this article, We are going to show you how to Extract Noun Phrases Using Term Extraction Transformation in SSIS with examples. Before reading this article, Please refer to the Term Extraction article for the definition, properties, and functionality of this Transformation.

The below screenshot shows our source data.

Source Table

Extract Noun Phrases Using Term Extraction Transformation in SSIS

STEP 1: Open BIDS and Drag and drop the data flow task from the toolbox to control flow. And rename it as Extracting Noun Phrases Using Term Extraction Transformation in SSIS.

Extract Noun Phrases Using Term Extraction Transformation in SSIS 1

Double click on it, and it will open the data flow tab. For more Transformations >> Click Here.

STEP 2: Drag and drop OLE DB Source, Term Extraction Transformation, and OLE DB Destination from the toolbox to the data flow region

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STEP 3: Double click on the OLE DB source in the data flow region will open the connection manager settings and provides space to write our SQL statement.

OLE DB Source Editor 3

Here we selected the Database as our source database, and the SQL Command we used in the above screenshot is:

SELECT [Player Information]
FROM [Term Extraction Transformation Source]

STEP 4: Click on the columns tab to verify the columns or uncheck the unwanted columns.

Available External Columns 4

Drag the OLE DB source output arrow onto the Term Extraction Transformation to transform the source Data.

SSIS Extract Noun Phrases

STEP 5: Double click on the Term Extraction Transformation and opens the Editor to configure it. Within the Term Extraction tab, choose the column you want to use for the Term Extraction from the available input columns. We left the output column names to default Term and Score.

Extract Noun Phrases Using Term Extraction Transformation in SSIS 5

Exclusion Tab: If you want to omit specific terms while term extraction, configure this Tab by naming a column with exclusion terms.

Extract Noun Phrases Using Term Extraction Transformation in SSIS 6

In this example, let us leave this because we want to extract all the Noun Phrases from the SSIS source data.

STEP 6: Advanced tab of the Term Extraction Transformation is vital to select Term Type, Source Type, and Frequency Threshold. In this example, we are extracting Noun Phrases only. So, we selected Noun Phrases as term types and selected the Frequency Threshold as 1. Please refer Extract Nouns Using Term Extraction Transformation article to understand, How to Extract Nouns from the Source Data. Also, refer to Extract Nouns and Noun Phrases and Exclusion Tab articles.

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From the below screenshot, there is a warning sign on the Term Extraction Transformation. It states that the error output is not connected. You can eliminate the warning symbol by configuring the error output. So double-click on the Configure Error Output button will open a new window to set the error output.

The default configuration of a Term Extraction Transformation is to redirect error rows. You can get rid of this warning by connecting the error output or by altering the default mode to Ignore Failure or Fail Component. Let’s change to Ignore Failure.

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Click ok to finish configuring the Term Extraction Transformation.

STEP 7: Next, provide the Server, database, and table details of the target. So double-click on the OLE DB Destination and provide the required information.

OLE DB Destination Editor 9

Here we selected the following database as the destination data source (localhost as server instance) and [Extracting Noun Phrases using Term Extraction] table as our destination table

STEP 8: Click on the Mappings tab to verify whether the source columns are mapped to the target columns. If not, please assign them to the proper destination column.

Column Mapping 10

Click ok to finish designing our SSIS Extracting Noun Phrases using the Term Extraction Transformation package. Let us run the package

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Let’s open the SQL Server Management Studio and check the results

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