Triple

T4183273
Position Surface form Disambiguated ID Type / Status
Subject Lübars E88245 entity
Predicate borderedBy P224 FINISHED
Object Blankenburg E545808 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: Blankenburg | Statement: [Lübars, borderedBy, Blankenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blankenburg
Context triple: [Lübars, borderedBy, Blankenburg]
  • A. Blankenburg chosen
    Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
  • B. Warffum
    Warffum is a historic village in the Dutch province of Groningen, known for its traditional architecture and open-air museum showcasing rural life.
  • C. Sassenheim
    Sassenheim is a town in the Dutch province of South Holland, known historically for its bulb-growing industry and location within the Duin- en Bollenstreek (Dune and Bulb Region).
  • D. Nieuwenhoorn
    Nieuwenhoorn is a village in the western Netherlands that forms part of the province of South Holland.
  • E. Stadshagen
    Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0307a0b481909c7287402a8c78c4 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097a5c6a4819082f4b9bf113ea33b completed March 23, 2026, 1:30 a.m.
Created at: March 9, 2026, 3:45 p.m.