Triple

T12191800
Position Surface form Disambiguated ID Type / Status
Subject Eidelstedt station E290480 entity
Predicate hasStationCode P1289 FINISHED
Object Eidelstedt E902277 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: Eidelstedt | Statement: [Eidelstedt station, hasStationCode, Eidelstedt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eidelstedt
Context triple: [Eidelstedt station, hasStationCode, Eidelstedt]
  • A. Eidelstedt chosen
    Eidelstedt is a district in the northwestern part of Hamburg, Germany, known for its residential areas and local shopping centers.
  • B. Hollenstedt
    Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
  • C. Schwarmstedt
    Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
  • D. Stettfeld
    Stettfeld is a municipality in the Haßberge district of Bavaria, Germany, known for its rural character and Franconian cultural heritage.
  • E. Wallhausen
    Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c54a4648190ad0f84c229534155 completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e5289608190bded58513316b1e5 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:50 p.m.