Triple

T10547569
Position Surface form Disambiguated ID Type / Status
Subject Peacock Theater E248861 entity
Predicate previousNamingRightsHolder P23950 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: [Peacock Theater, previousNamingRightsHolder, Microsoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft
Context triple: [Peacock Theater, previousNamingRightsHolder, 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. WIN Corporation
    WIN Corporation is an Australian media company best known for owning and operating the WIN Television network and related broadcasting assets.
  • D. Microsoft Auto
    Microsoft Auto is an embedded automotive software platform developed by Microsoft to power in-car infotainment and navigation systems.
  • E. 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.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d20ef48190ab9f70d4ce5f2a11 completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d93457af7c819090f576ae606c5849 completed April 10, 2026, 5:33 p.m.
Created at: April 6, 2026, 12:33 p.m.