Triple
T7985032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Machine Learning |
E185664
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Azure Data Lake Storage |
E185662
|
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 Data Lake Storage | Statement: [Azure Machine Learning, integratesWith, Azure Data Lake Storage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azure Data Lake Storage Context triple: [Azure Machine Learning, integratesWith, Azure Data Lake Storage]
-
A.
Azure Data Lake Storage
chosen
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.
-
B.
Azure Blob Storage
Azure Blob Storage is a cloud-based object storage service for storing and managing large amounts of unstructured data such as text and binary files.
-
C.
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.
-
D.
Azure HDInsight
Azure HDInsight is a fully managed cloud service from Microsoft that provides scalable Apache Hadoop, Spark, Hive, and other big data frameworks for processing and analyzing large datasets.
-
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_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_69cc938ffbb481908c4540e560469777 |
completed | April 1, 2026, 3:40 a.m. |
Created at: March 30, 2026, 5:15 p.m.