Triple
T9899323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure IoT Hub |
E182245
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Azure Stream Analytics |
E705282
|
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 Stream Analytics | Statement: [Azure IoT Hub, integratesWith, Azure Stream Analytics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azure Stream Analytics Context triple: [Azure IoT Hub, integratesWith, Azure Stream Analytics]
-
A.
Azure Stream Analytics
chosen
Azure Stream Analytics is a real-time analytics and complex event processing service in Microsoft Azure that ingests and analyzes streaming data from various sources to generate timely insights and actions.
-
B.
Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics is a fully managed AWS service that enables real-time processing and analysis of streaming data using SQL or Apache Flink.
-
C.
Azure Event Hubs
Azure Event Hubs is a fully managed, real-time data ingestion and streaming platform on Microsoft Azure designed to handle millions of events per second for analytics and processing.
-
D.
Azure Time Series Insights
Azure Time Series Insights is a fully managed analytics, storage, and visualization service for exploring and analyzing time-series data from IoT and other event streams in real time.
-
E.
Azure Data Factory
Azure Data Factory is a cloud-based data integration service from Microsoft that enables users to create, schedule, and orchestrate data pipelines for moving and transforming data at scale across diverse sources.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4adc03481909e0f657db01e5bab |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20d92624c81909f5a8af8703ead09 |
completed | April 5, 2026, 7:21 a.m. |
Created at: March 30, 2026, 8:40 p.m.