Triple
T7984899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Data Lake Storage |
E185662
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object |
Azure Stream Analytics
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.
|
E705282
|
NE FINISHED |
How this triple was built (4 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 Data Lake Storage, integratesWith, Azure Stream Analytics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azure Stream Analytics Context triple: [Azure Data Lake Storage, integratesWith, Azure Stream Analytics]
-
A.
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.
-
B.
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.
-
C.
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.
-
D.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
-
E.
Azure Data Lake Storage
Azure Data Lake Storage is a scalable, secure cloud-based data lake service from Microsoft designed for big data analytics and enterprise data warehousing workloads.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Azure Stream Analytics Triple: [Azure Data Lake Storage, integratesWith, Azure Stream Analytics]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Azure Stream Analytics Target entity description: 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.
-
A.
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.
-
B.
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.
-
C.
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.
-
D.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
-
E.
Azure Data Lake Storage
Azure Data Lake Storage is a scalable, secure cloud-based data lake service from Microsoft designed for big data analytics and enterprise data warehousing workloads.
- F. None of above. chosen
Provenance (5 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c4a55b881909a96133e56c0dffa |
completed | March 31, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0e0b2748190930c22c6157d1b07 |
completed | March 31, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_69cc46c221848190848c7e017e532a16 |
completed | March 31, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc480d2f40819085046a1d0c9d05e0 |
completed | March 31, 2026, 10:17 p.m. |
Created at: March 30, 2026, 5:15 p.m.