Triple
T7932057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloud Functions |
E184210
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Azure Functions |
E182240
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Azure Functions | Statement: [Cloud Functions, competesWith, Azure Functions]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azure Functions Context triple: [Cloud Functions, competesWith, Azure Functions]
-
A.
Azure Functions
chosen
Azure Functions is a serverless compute service that lets developers run event-driven code on demand in the cloud without managing infrastructure.
-
B.
Cloud Functions
Cloud Functions is Google Cloud’s serverless compute platform for running event-driven code without managing servers.
-
C.
Azure App Service
Azure App Service is a fully managed platform-as-a-service (PaaS) offering from Microsoft Azure for building, deploying, and scaling web apps and APIs.
-
D.
AWS Lambda
AWS Lambda is a serverless compute service that lets developers run code in response to events without provisioning or managing servers.
-
E.
Azure Logic Apps
Azure Logic Apps is a cloud-based service for building and running automated workflows that integrate apps, data, services, and systems through a visual designer and prebuilt connectors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3ace87f081908635769942645e78 |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c041e588190bfbf251ed88d5bcd |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:07 p.m.