Creating an entity for price is a feature of Conversational Language Understanding (CLU/LUIS), not Question Answering. Custom question answering does not use entities for extraction or intent resolution; it matches user utterances to Q/A pairs using alternates, synonyms, and ranking. Therefore, defining an "entity for price" would not make the chatbot correctly answer "How much does < product > cost?". The correct fix is to author additional alternate phrasings (as in Q266).
References
Custom question answering capabilities (no entity modeling).
https://learn.microsoft.com/azure/ai-services/language-service/question-answering/overview CLU entities vs. QnA authoring-separate features and workflows.
https://learn.microsoft.com/azure/ai-services/language-service/conversational-language-understanding
/overview

Explanation:

To detect aggressive language (e.g., profanity/abuse) and sexually explicit content in text using the Content Moderator Text - Screen API:
classify = true
Enables machine-assisted text classification that returns category scores (e.g., sexually explicit/suggestive categories). This is required to identify sexual content.
language = < code > (for example, eng )
Specifies the language so profanity/abusive terms are detected correctly. The profanity detection in Text- Screen is language dependent.
autocorrect = true
Helps normalize intentionally misspelled or obfuscated words so that profanity or aggressive terms are still detected (e.g., "f@#$" # "fuck").
Other parameters in the blade are not necessary for this goal:
PII targets personal data extraction, not aggression/sexuality.
listId is for matching against custom blocklists.
Headers like Ocp-Apim-Subscription-Key and Content-Type are required to call the API, but they are not the content-analysis settings that control detection behavior asked for in this question.
Microsoft Azure AI References
Azure AI Content Moderator - Screen text API parameters (autocorrect, language, classify) and category outputs.
Azure AI Content Moderator - Text moderation concepts: profanity detection and classification categories.

This question is about selecting valid training files for a custom Form Recognizer model in Azure AI Document Intelligence (formerly Form Recognizer).
Supported File Formats for Training
According to Microsoft documentation, Form Recognizer supports the following for training and analysis:
PDF (# 500 pages, # 50 MB for training)
JPEG/JPG (# 50 MB)
PNG (# 50 MB)
TIFF (# 50 MB)
Unsupported:
MP4 # Video not supported.
GIF # Not supported.
Maximum File Size Rules (for training input files):
Images (JPG, PNG, TIFF): # 50 MB
PDFs: # 50 MB
Note: 500 pages limit applies to PDFs.
File-by-File Analysis
File1 - PDF - 20 MB
Type supported.
Size within limit ( < 50 MB).
Valid #
File2 - MP4 - 100 MB
MP4 is not supported.
Invalid #
File3 - JPG - 20 MB
Type supported.
Size within limit ( < 50 MB).
Valid #
File4 - PDF - 100 MB
Type supported.
Size exceeds the 50 MB maximum limit.
Invalid #
File5 - GIF - 1 MB
GIF format not supported.
Invalid #
File6 - JPG - 40 MB
Type supported.
Size within limit ( < 50 MB).
Valid #
The Answer:
A). File1, C. File3, F. File6
Microsoft References
Azure AI Document Intelligence (Form Recognizer) - Supported file formats Train a custom model with Azure Form Recognizer

Explanation:

Code Recap
static void GetKeyPhrases ( TextAnalyticsClient textAnalyticsClient, string text)
{
var response = textAnalyticsClient.ExtractKeyPhrases(text);
Console.WriteLine( " Key phrases: " );
foreach ( string keyphrase in response.Value)
{
Console.WriteLine( $ " \t {keyphrase} " );
}
}
Then called with:
GetKeyPhrases(textAnalyticsClient, " the cat sat on the mat " );
Statement Analysis
"The call will output key phrases from the input string to the console." Yes.
The method calls ExtractKeyPhrases , iterates over response.Value , and writes each key phrase to the console.
"The output will contain the following words: the, cat, sat, on, and mat." No.
The Text Analytics key phrase extraction returns meaningful phrases, not stop words or every word.
Likely result: " cat " , " mat " , maybe " sat " depending on language model. But not " the " , " on " .
"The output will contain the confidence level for key phrases."
No.
The ExtractKeyPhrases method in Text Analytics API returns only key phrases as strings, not confidence scores.
Final Answer
The call will output key phrases from the input string to the console # Yes The output will contain the following words: the, cat, sat, on, and mat # No The output will contain the confidence level for key phrases # No Microsoft References Azure Text Analytics - Key Phrase Extraction TextAnalyticsClient.ExtractKeyPhrases

Explanation:

To validate that an input language is supported for translation, call the Translator SDK's GetLanguagesAsync with scope: " translation " to retrieve the supported languages. The call returns a GetLanguagesResult, whose Translation property is a dictionary keyed by language codes (e.g., " en " , " it " ). You can then check membership with ContainsKey(language) . If the key exists, the language is supported; otherwise, it isn't.
This matches the .NET Translator client design:
TextTranslationClient.GetLanguagesAsync(...) fetches supported languages.
GetLanguagesResult.Translation is a dictionary of translation-capable languages, so ContainsKey is the correct check.
Microsoft References
TextTranslationClient.GetLanguagesAsync (overview and signature).
Languages REST reference - use scope=translation to get languages supported for translation. Microsoft Learn GetLanguagesResult class - Translation dictionary property.