Triple

T6304149
Position Surface form Disambiguated ID Type / Status
Subject Vestre Aker E141330 entity
Predicate contains P35 FINISHED
Object Vinderen E573430 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: Vinderen | Statement: [Vestre Aker, contains, Vinderen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vinderen
Context triple: [Vestre Aker, contains, Vinderen]
  • A. Vinderen chosen
    Vinderen is a residential neighborhood in Oslo, Norway, known for its affluent character, green surroundings, and convenient access to the city center.
  • B. De Wilp
    De Wilp is a village in the Dutch province of Groningen, known for its rural character and location near the border with Friesland.
  • C. The Van
    "The Van" is a 1996 Irish comedy-drama film, based on Roddy Doyle’s novel, about two friends who start a fish-and-chip van business in Dublin after one of them loses his job.
  • D. The Happy Hunting-Grounds
    The Happy Hunting-Grounds is a travel and adventure book by Kermit Roosevelt recounting his experiences and observations during expeditions in the American West.
  • E. Ringsaker
    Ringsaker is a municipality in Innlandet county, Norway, known for its agricultural landscapes along Lake Mjøsa and its proximity to the town of Hamar.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0645f26a881909d5746151c0843cc completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e43e085081908546fa120a43bf84 completed March 27, 2026, 1:58 a.m.
Created at: March 22, 2026, 4:28 p.m.