Triple

T3033597
Position Surface form Disambiguated ID Type / Status
Subject Philippe Starck E82953 entity
Predicate designedForBrand P9494 FINISHED
Object Microsoft E1649 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 | Statement: [Philippe Starck, designedForBrand, Microsoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft
Context triple: [Philippe Starck, designedForBrand, Microsoft]
  • A. Microsoft chosen
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • B. Micros Systems
    Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
  • C. Microsoft Office
    Microsoft Office is a widely used suite of productivity applications developed by Microsoft, including programs for word processing, spreadsheets, presentations, email, and more.
  • D. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • E. Microsoft Mobile
    Microsoft Mobile was the Microsoft-owned division responsible for designing, manufacturing, and marketing Lumia smartphones and other mobile devices following the acquisition of Nokia’s handset business.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9af13ce48190bda4f5ca0ffe6285 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1dec30d8081909d6ee691e5e51434 completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.