Which of the following statements is true regarding reviewing and applying entities in UiPath Communications Mining?

A single entity value can be split across multiple paragraphs.
If the entity value is correctly predicted, but the entity type is wrong, it cannot be changed.
All of the entities within a paragraph should be reviewed.
All of the entities in a communication must be reviewed.

Answer(s): C

What happens during the Classify stage of the Document Understanding Framework?

The OCR engine is used to extract text from the image document.
The extracted data is exported as a dataset.
The target fields are extracted from the document and sent to Action Center for human validation.
The documents are included in one of the taxonomy document types or skipped.

Answer(s): D

Which of the following is a best practice when choosing a UiPath ML (Machine Learning) Extractor?

The popularity of the ML Extractor among other UiPath users should be the primary factor when choosing a UiPath ML Extractor.
Opt for the ML Extractor that has the highest number of downloads or positive reviews.
Consider the document types, language, and data quality when choosing an ML Extractor.
It is important to select one that is specifically trained or optimized for the document types being processed.
It is also important to take into account the quality and diversity of the training data used to train the ML Extractor to ensure accurate and reliable extraction results.
The cost of the ML Extractor should be the main consideration when choosing an ML Extractor.
Select the ML Extractor that offers the lowest price, regardless of its performance or suitability for the specific document understanding needs.
The size of the ML Extractor is the most important factor to consider when choosing an ML Extractor.
Bigger models always perform better and provide more accurate extraction results because the development team invested time and effort into creating the algorithm, which in turn will result in better performance for the trained model.

Answer(s): B

Which of the following extractors can be used for Data Extraction Scope activity?

Intelligent Form Extractor, Machine Learning Extractor, Logic Extractor, and Regex Based Extractor.
Full Extractor, Machine Learning Extractor, Intelligent Form Extractor, and Regex Based Extractor.
Form Extractor, Incremental Extractor, Machine Learning Extractor, and Intelligent Form Extractor.
Regex Based Extractor, Form Extractor, Intelligent Form Extractor, and Machine Learning Extractor.

Answer(s): D

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