Valid GES-C01 Dumps shared by EduDump.com for Helping Passing GES-C01 Exam! EduDump.com now offer the newest GES-C01 exam dumps, the EduDump.com GES-C01 exam questions have been updated and answers have been corrected get the newest EduDump.com GES-C01 dumps with Test Engine here:
A Gen AI Specialist is leveraging Snowflake Document AI to extract specific entities and table data from a large and varied collection of documents. They are aware of potential limitations and want to understand the expected outcomes when processing different types of files. Considering a scenario where a Document AI model build is used with the '!PREDICT' method, which of the following statements accurately describe the expected behavior or potential issues based on Document AI's conditions and limitations?
Correct Answer: A,D
Option A is correct. Document AI documents must be no more than 125 pages long. A 130-page document would exceed this limit, leading to an error such as 'Document has too many pages. Actual: 150. Maximum: 125.'. Option B is incorrect. If the Document AI model does not find an answer in the document, the model does not return a 'value' key. It only retums the 'score' key, which indicates how confident the model is that the document does not contain the answer. Option C is incorrect. Document AI supports processing documents in English, Spanish, French, German, Portuguese, Italian, and Polish, but notes that results for other languages might not be satisfactory. Ukrainian is not listed among the supported languages. Option D is correct. The sources state that in table extraction, if a cell is empty, the Document AI model does not return a 'value' key but does return the 'score' key, which indicates how confident the model is that the cell is empty. This is illustrated in the example output for 'tablel Itak and 'table21date' . Option E is incorrect. For general entity extraction, the Document AI model returns answers that are up to 512 tokens long (about 320 words) per question. The 2048-token limit applies specifically to answers from the model for table extraction.