Triple

T2432832
Position Surface form Disambiguated ID Type / Status
Subject Xbox Game Studios E52885 entity
Predicate parentOrganization P254 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: [Xbox Game Studios, parentOrganization, Microsoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft
Context triple: [Xbox Game Studios, parentOrganization, 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9c915e881908d97ae4ccc83ab53 completed March 7, 2026, 6:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf5e33208190a6899e6672b3daeb completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:43 p.m.