Triple

T1621305
Position Surface form Disambiguated ID Type / Status
Subject Power Automate E35036 entity
Predicate integratesWith P1075 FINISHED
Object Power BI E5276 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: Power BI | Statement: [Power Automate, integratesWith, Power BI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Power BI
Context triple: [Power Automate, integratesWith, Power BI]
  • A. Power BI chosen
    Power BI is a Microsoft business analytics and data visualization platform used to transform, analyze, and present data through interactive dashboards and reports.
  • B. Power View
    Power View is an interactive data visualization and reporting tool from Microsoft that enables users to create dynamic, presentation-ready dashboards and reports.
  • C. Power BI Gateway
    Power BI Gateway is an on-premises data gateway that securely connects local data sources to Microsoft Power BI and other cloud services for refresh and live queries.
  • D. Power BI Embedded
    Power BI Embedded is a Microsoft Azure service that lets developers integrate interactive Power BI reports and dashboards into their own applications.
  • E. Power Pivot
    Power Pivot is an Excel data modeling and analysis add-in that enables users to create sophisticated data models, relationships, and DAX calculations for business intelligence reporting.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909b1fc788190b38c0aa4ccc2e953 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51d2cbb481908bc74cecdc023547 completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.