Azure Form Recognizer
E828315
Azure Form Recognizer is a cloud-based AI service that uses machine learning to extract structured data, text, and key-value pairs from documents and forms.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Azure Form Recognizer canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9899263 — 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: Azure Form Recognizer Context triple: [Azure Cognitive Services, includesService, Azure Form Recognizer]
-
A.
LayoutLM
LayoutLM is a transformer-based document understanding model that jointly leverages text, layout, and visual information to process and analyze scanned documents and forms.
-
B.
DocSend
DocSend is a document-sharing and tracking platform designed for securely sending files and gaining analytics on how recipients engage with them.
-
C.
Adobe Scan
Adobe Scan is a mobile scanning app by Adobe that converts physical documents into high-quality PDFs and integrates with Adobe’s cloud-based document services.
-
D.
Office Lens
Office Lens is a Microsoft mobile scanning app that captures documents, whiteboards, and other content with a device camera and converts them into editable, shareable digital files.
-
E.
Adobe Document Cloud
Adobe Document Cloud is Adobe’s integrated suite of cloud-based services and apps for creating, editing, managing, and securely sharing PDF documents across devices.
- 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: Azure Form Recognizer Target entity description: Azure Form Recognizer is a cloud-based AI service that uses machine learning to extract structured data, text, and key-value pairs from documents and forms.
-
A.
LayoutLM
LayoutLM is a transformer-based document understanding model that jointly leverages text, layout, and visual information to process and analyze scanned documents and forms.
-
B.
DocSend
DocSend is a document-sharing and tracking platform designed for securely sending files and gaining analytics on how recipients engage with them.
-
C.
Adobe Scan
Adobe Scan is a mobile scanning app by Adobe that converts physical documents into high-quality PDFs and integrates with Adobe’s cloud-based document services.
-
D.
Office Lens
Office Lens is a Microsoft mobile scanning app that captures documents, whiteboards, and other content with a device camera and converts them into editable, shareable digital files.
-
E.
Adobe Document Cloud
Adobe Document Cloud is Adobe’s integrated suite of cloud-based services and apps for creating, editing, managing, and securely sharing PDF documents across devices.
- F. None of above. chosen
Statements (70)
| Predicate | Object |
|---|---|
| instanceOf |
Azure Cognitive Service
ⓘ
cloud-based AI service ⓘ document intelligence service ⓘ |
| accessedVia |
REST API
ⓘ
client SDKs ⓘ |
| belongsToCategory |
AI-powered OCR service
ⓘ
document processing ⓘ intelligent document processing ⓘ |
| deploymentModel | fully managed cloud service ⓘ |
| developedBy | Microsoft ⓘ |
| hasCapability |
analyze document structure
ⓘ
classify documents ⓘ extract key-value pairs ⓘ extract layout information ⓘ extract named fields ⓘ extract selection marks ⓘ extract tables ⓘ extract text from documents ⓘ process business cards ⓘ process custom forms ⓘ process forms ⓘ process identity documents ⓘ process invoices ⓘ process receipts ⓘ return bounding boxes ⓘ return confidence scores ⓘ return page-level metadata ⓘ support asynchronous document processing ⓘ support batch document processing ⓘ support composed models ⓘ support custom models ⓘ support human-in-the-loop review ⓘ support model labeling ⓘ support model training ⓘ support prebuilt models ⓘ |
| hasSDK |
Azure Form Recognizer .NET SDK
NERFINISHED
ⓘ
Azure Form Recognizer Java SDK NERFINISHED ⓘ Azure Form Recognizer JavaScript SDK NERFINISHED ⓘ Azure Form Recognizer Python SDK NERFINISHED ⓘ |
| integratesWith |
Azure Portal
NERFINISHED
ⓘ
Azure Storage NERFINISHED ⓘ Logic Apps NERFINISHED ⓘ Power Apps NERFINISHED ⓘ Power Automate NERFINISHED ⓘ |
| partOf |
Azure AI services
NERFINISHED
ⓘ
Microsoft Azure NERFINISHED ⓘ |
| pricingModel | pay-as-you-go ⓘ |
| securityFeature |
data encryption at rest
ⓘ
data encryption in transit ⓘ role-based access control ⓘ |
| supportsFeature |
custom form model
ⓘ
document classification model ⓘ handwritten text recognition ⓘ key-value pair extraction ⓘ prebuilt ID document model ⓘ prebuilt business card model ⓘ prebuilt invoice model ⓘ prebuilt layout model ⓘ prebuilt receipt model ⓘ printed text recognition ⓘ table extraction ⓘ |
| supportsInputFormat |
BMP
ⓘ
JPEG ⓘ PDF ⓘ PNG ⓘ TIFF ⓘ |
| supportsLanguage |
English
ⓘ
multiple languages ⓘ |
| uses |
machine learning
ⓘ
optical character recognition ⓘ |
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: Azure Form Recognizer Description of subject: Azure Form Recognizer is a cloud-based AI service that uses machine learning to extract structured data, text, and key-value pairs from documents and forms.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.