Triple

T277325
Position Surface form Disambiguated ID Type / Status
Subject Power BI E5276 entity
Predicate integratesWith P1075 FINISHED
Object Microsoft Excel E5278 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: Microsoft Excel | Statement: [Power BI, integratesWith, Microsoft Excel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft Excel
Context triple: [Power BI, integratesWith, Microsoft Excel]
  • A. Excel chosen
    Excel is a widely used spreadsheet software by Microsoft that enables data organization, analysis, visualization, and basic to advanced analytics through formulas, functions, and tools like PivotTables.
  • B. Lotus 1-2-3
    Lotus 1-2-3 is a pioneering spreadsheet software program for personal computers that became a dominant business application in the 1980s.
  • C. Microsoft 365
    Microsoft 365 is a subscription-based suite of productivity and collaboration tools that combines Office applications with cloud services, security features, and device management.
  • D. PowerPoint
    PowerPoint is a widely used Microsoft presentation software application for creating, editing, and delivering slide-based visual presentations.
  • E. Tableau
    Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39153528c8190a0f1e69a3f94b305 completed March 1, 2026, 1:07 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.