Triple

T15375188
Position Surface form Disambiguated ID Type / Status
Subject WIN Entertainment Centre E367648 entity
Predicate namedAfter P63 FINISHED
Object WIN Corporation E423768 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: WIN Corporation | Statement: [WIN Entertainment Centre, namedAfter, WIN Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WIN Corporation
Context triple: [WIN Entertainment Centre, namedAfter, WIN Corporation]
  • A. WIN Corporation chosen
    WIN Corporation is an Australian media company best known for owning and operating the WIN Television network and related broadcasting assets.
  • 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
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • D. Unisys
    Unisys is an American global information technology company known for providing IT services, software, and infrastructure solutions to government and commercial clients.
  • E. Roland Systems Group
    Roland Systems Group is a professional audio and video equipment division of Roland Corporation, specializing in live production, mixing, and recording solutions.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e5d6f808190b0a4cdb35dc89e69 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b5502508190bd39b6d81ee57cc0 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:18 a.m.