Triple

T7460144
Position Surface form Disambiguated ID Type / Status
Subject Batwing E176224 entity
Predicate manufacturer P490 FINISHED
Object Vekoma E232240 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: Vekoma | Statement: [Batwing, manufacturer, Vekoma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vekoma
Context triple: [Batwing, manufacturer, Vekoma]
  • A. Vekoma chosen
    Vekoma is a Dutch roller coaster and amusement ride manufacturer known worldwide for designing and building a wide range of thrill and family attractions for theme parks.
  • B. Vaala
    Vaala is a municipality in northern Finland known for its lakeside landscapes and location along the Oulujoki river.
  • C. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • D. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • E. Volkerak
    Volkerak is a lake and former estuarine channel in the southwestern Netherlands that forms part of the country’s major Rhine–Meuse–Scheldt waterway system.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d525708190b7838e07ac2fbe1f completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8345f629c8190889081e18bdfe6f7 completed March 28, 2026, 8:04 p.m.
Created at: March 27, 2026, 3:38 p.m.