Triple

T16688204
Position Surface form Disambiguated ID Type / Status
Subject Friesland district E405521 entity
Predicate contains P35 FINISHED
Object Schortens E671077 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: Schortens | Statement: [Friesland district, contains, Schortens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schortens
Context triple: [Friesland district, contains, Schortens]
  • A. Schortens chosen
    Schortens is a small town in the district of Friesland in Lower Saxony, northwestern Germany, near the North Sea coast.
  • B. Schnelsen
    Schnelsen is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to major transport routes.
  • C. Wiedensahl
    Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
  • D. Roderesch
    Roderesch is a small village in the municipality of Noordenveld in the province of Drenthe in the northeastern Netherlands.
  • E. Schellerten
    Schellerten is a rural municipality in Lower Saxony, Germany, characterized by its agricultural landscape and small-village communities.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea75df481909a7ebb9b2a9d0afd completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a45af7c8190bfe09dd0e0573573 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.