Triple

T1668905
Position Surface form Disambiguated ID Type / Status
Subject Power View E36076 entity
Predicate dataSource P409 FINISHED
Object PowerPivot E36149 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: PowerPivot | Statement: [Power View, dataSource, PowerPivot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PowerPivot
Context triple: [Power View, dataSource, PowerPivot]
  • A. Power Pivot chosen
    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.
  • 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 Query
    Power Query is a data connection and transformation tool used to import, clean, and reshape data from various sources before analysis in Microsoft Power BI and other Microsoft products.
  • D. Power BI
    Power BI is a Microsoft business analytics and data visualization platform used to transform, analyze, and present data through interactive dashboards and reports.
  • E. SQL Server Analysis Services Tabular
    SQL Server Analysis Services Tabular is a Microsoft in-memory analytical engine for building tabular data models that support fast, interactive business intelligence and 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adf3d3c81909233e574e79b82a2 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad7988bda081908a966ae1f589cb8f completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:29 p.m.