Text Parse Action Set: Syntax
Provides actions for parsing, accumulating results, handling misspellings, and applying word vector models to score documents
tpWordVector Action
Applies a word vector model to score documents. This action requires a SAS Visual Text Analytics license.
| See: | Using the tpWordVector Action |
|---|---|
| Example: | Apply a Word Vector Model to Score Documents and Train a Recurrent Neural Network (RNN) Model Using the tpWordVector Action |
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametermodelTable |
— |
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word. |
|
required parametertable |
— |
specifies an input CAS table that is the tpParse output offset table |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametercasOut |
— |
specifies an output CAS table that contains the word embedding scoring result |
Parameter Descriptions
* casOut={casouttable}
specifies an output CAS table that contains the word embedding scoring result
For more information about specifying the casOut parameter, see the common casouttable parameter.
* modelTable={castable}
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word.
For more information about specifying the modelTable parameter, see the common castable (Form 1) parameter.
| Alias | model |
|---|
* table={castable}
specifies an input CAS table that is the tpParse output offset table
For more information about specifying the table parameter, see the common castable (Form 1) parameter.
| Aliases | offset |
|---|---|
| offsetTable |
tpWordVector Action
Applies a word vector model to score documents. This action requires a SAS Visual Text Analytics license.
| See: | Using the tpWordVector Action |
|---|---|
| Example: | Apply a Word Vector Model to Score Documents and Train a Recurrent Neural Network (RNN) Model Using the tpWordVector Action |
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametermodelTable |
— |
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word. |
|
required parametertable |
— |
specifies an input CAS table that is the tpParse output offset table |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametercasOut |
— |
specifies an output CAS table that contains the word embedding scoring result |
Parameter Descriptions
* casOut={casouttable}
specifies an output CAS table that contains the word embedding scoring result
For more information about specifying the casOut parameter, see the common casouttable parameter.
* modelTable={castable}
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word.
For more information about specifying the modelTable parameter, see the common castable (Form 1) parameter.
| Alias | model |
|---|
* table={castable}
specifies an input CAS table that is the tpParse output offset table
For more information about specifying the table parameter, see the common castable (Form 1) parameter.
| Aliases | offset |
|---|---|
| offsetTable |
tpWordVector Action
Applies a word vector model to score documents. This action requires a SAS Visual Text Analytics license.
| See: | Using the tpWordVector Action |
|---|---|
| Example: | Apply a Word Vector Model to Score Documents and Train a Recurrent Neural Network (RNN) Model Using the tpWordVector Action |
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametermodelTable |
— |
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word. |
|
required parametertable |
— |
specifies an input CAS table that is the tpParse output offset table |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametercasOut |
— |
specifies an output CAS table that contains the word embedding scoring result |
Parameter Descriptions
* casOut={casouttable}
specifies an output CAS table that contains the word embedding scoring result
For more information about specifying the casOut parameter, see the common casouttable parameter.
* modelTable={castable}
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word.
For more information about specifying the modelTable parameter, see the common castable (Form 1) parameter.
| Alias | model |
|---|
* table={castable}
specifies an input CAS table that is the tpParse output offset table
For more information about specifying the table parameter, see the common castable (Form 1) parameter.
| Aliases | offset |
|---|---|
| offsetTable |
tpWordVector Action
Applies a word vector model to score documents. This action requires a SAS Visual Text Analytics license.
| See: | Using the tpWordVector Action |
|---|---|
| Example: | Apply a Word Vector Model to Score Documents and Train a Recurrent Neural Network (RNN) Model Using the tpWordVector Action |
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametermodelTable |
— |
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word. |
|
required parametertable |
— |
specifies an input CAS table that is the tpParse output offset table |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parametercasOut |
— |
specifies an output CAS table that contains the word embedding scoring result |
Parameter Descriptions
* casOut=list(casouttable)
specifies an output CAS table that contains the word embedding scoring result
For more information about specifying the casOut parameter, see the common casouttable parameter.
* modelTable=list(castable)
specifies an input word embedding CAS table that contains numeric vector representations of words trained based on a large corpus, typically without any label information. When using word embeddings, any column name can be used in the embedding table, but the first column of the embedding table must be the word and the rest of the columns are treated as numeric vector representations of that word.
For more information about specifying the modelTable parameter, see the common castable (Form 1) parameter.
| Alias | model |
|---|
* table=list(castable)
specifies an input CAS table that is the tpParse output offset table
For more information about specifying the table parameter, see the common castable (Form 1) parameter.
| Aliases | offset |
|---|---|
| offsetTable |