QnA Maker
E828316
QnA Maker is a cloud-based Azure Cognitive Service that lets developers build, train, and deploy question-answering knowledge bases from FAQs and other content using natural language processing.
All labels observed (1)
| Label | Occurrences |
|---|---|
| QnA Maker canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9899267 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: QnA Maker Context triple: [Azure Cognitive Services, includesService, QnA Maker]
-
A.
Power Virtual Agents
Power Virtual Agents is a Microsoft low-code platform service for building and deploying AI-powered chatbots that can interact with users across websites, apps, and messaging channels.
-
B.
Dialogflow
Dialogflow is a Google Cloud service for building conversational interfaces, such as chatbots and voice apps, that understand natural language.
-
C.
Meta AI assistant
Meta AI assistant is an artificial intelligence–powered virtual assistant created by Meta to help users with tasks like answering questions, generating content, and interacting across Meta’s platforms.
-
D.
Libera Chat
Libera Chat is a prominent free and open-source–focused IRC network that hosts real-time discussion channels for numerous software projects and online communities.
-
E.
OpenAI Chat Completions API
The OpenAI Chat Completions API is a cloud-based interface that lets developers integrate advanced conversational AI models into their applications for tasks like dialogue, assistance, and content generation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: QnA Maker Target entity description: QnA Maker is a cloud-based Azure Cognitive Service that lets developers build, train, and deploy question-answering knowledge bases from FAQs and other content using natural language processing.
-
A.
Power Virtual Agents
Power Virtual Agents is a Microsoft low-code platform service for building and deploying AI-powered chatbots that can interact with users across websites, apps, and messaging channels.
-
B.
Dialogflow
Dialogflow is a Google Cloud service for building conversational interfaces, such as chatbots and voice apps, that understand natural language.
-
C.
Meta AI assistant
Meta AI assistant is an artificial intelligence–powered virtual assistant created by Meta to help users with tasks like answering questions, generating content, and interacting across Meta’s platforms.
-
D.
Libera Chat
Libera Chat is a prominent free and open-source–focused IRC network that hosts real-time discussion channels for numerous software projects and online communities.
-
E.
OpenAI Chat Completions API
The OpenAI Chat Completions API is a cloud-based interface that lets developers integrate advanced conversational AI models into their applications for tasks like dialogue, assistance, and content generation.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
Azure Cognitive Service
ⓘ
cloud-based service ⓘ question answering service ⓘ |
| accessControl | Azure Active Directory NERFINISHED ⓘ |
| billingModel | consumption-based ⓘ |
| deploymentModel | cloud ⓘ |
| developedBy | Microsoft ⓘ |
| documentationUrl | https://learn.microsoft.com/azure/cognitive-services/qnamaker/overview ⓘ |
| hasPurpose |
build question answering knowledge bases
ⓘ
deploy question answering endpoints ⓘ train question answering models ⓘ |
| hasSuccessor | Azure Cognitive Service for Language question answering NERFINISHED ⓘ |
| hostedOn | Microsoft Azure NERFINISHED ⓘ |
| integratesWith |
Azure Bot Service
NERFINISHED
ⓘ
Azure Functions NERFINISHED ⓘ Microsoft Bot Framework NERFINISHED ⓘ Power Virtual Agents NERFINISHED ⓘ |
| ownedBy | Microsoft Corporation NERFINISHED ⓘ |
| partOf |
Azure Cognitive Services
NERFINISHED
ⓘ
Microsoft Azure NERFINISHED ⓘ |
| provides |
REST API
NERFINISHED
ⓘ
knowledge base management ⓘ question answering endpoint ⓘ web-based portal ⓘ |
| retiredOn | 2025-03-31 ⓘ |
| retirementAnnounced | 2021 ⓘ |
| status | retired ⓘ |
| supportsExport | knowledge base backup ⓘ |
| supportsFeature |
active learning
ⓘ
chit-chat personality packs ⓘ metadata-based filtering ⓘ multi-turn conversations ⓘ ranked answer selection ⓘ synonym management ⓘ |
| supportsImport |
Excel files
ⓘ
SharePoint FAQ pages ⓘ public website FAQs ⓘ |
| supportsInputType |
FAQ documents
ⓘ
URLs with FAQ content ⓘ product manuals ⓘ structured question-answer pairs ⓘ |
| supportsLanguage | multiple natural languages ⓘ |
| typicalUseCase |
FAQ bots
ⓘ
customer support virtual agents ⓘ internal knowledge assistants ⓘ |
| uses |
Azure Search
NERFINISHED
ⓘ
machine learning ⓘ natural language processing ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: QnA Maker Description of subject: QnA Maker is a cloud-based Azure Cognitive Service that lets developers build, train, and deploy question-answering knowledge bases from FAQs and other content using natural language processing.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.