Configure text extraction analysis by specifying tags, keywords, entity extraction models, and pattern extraction rules. Use tags and keywords to mark specific terms and their synonyms that you want to identify in the analyzed text. Text and pattern extraction models help to identify various types of named entities.
- In the Records navigation panel, click .
- Open the Text Analyzer rule that you want to configure.
- Perform any of the following actions:
- To detect the most relevant words or phrases in a document to, for example, create
word clouds or perform a faceted search, in the Text extraction
section, select the Enable auto-tag extraction check box and
perform one of the following actions:
- To detect all significant tags in the document, click Detect all tags.
- To detect a specific number of tags in the document, click Detect top N tag(s) and specify the number of tags that you want to detect.
- To summarize the text that you analyze, select the Enable
summarization check box and specify the compression ratio.
Note: The compression ratio is specific to your use case. For example, to create very short summaries of large bodies of text, you can specify the compression ratio as 1% to extract only the few most information-rich sentences.
- To extract named entities from text, select Enable text extraction.
- To detect the most relevant words or phrases in a document to, for example, create word clouds or perform a faceted search, in the Text extraction section, select the Enable auto-tag extraction check box and perform one of the following actions:
- If you selected the Enable text extraction, select an entity
model by performing the following actions:
- Click Add extraction model.
- In the Extraction model field, provide the name of the name of the entity extraction model to use for named entity extraction.
- Optional: To choose the detectable entity types in the model, select or clear the check box next to the applicable entity type.
- Click Submit to confirm your settings.
- Click Save to confirm your settings.