Triple

T13413567
Position Surface form Disambiguated ID Type / Status
Subject Mont-Saint-Aignan E320150 entity
Predicate hasTwinTown P919 FINISHED
Object Barsinghausen E334711 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: Barsinghausen | Statement: [Mont-Saint-Aignan, hasTwinTown, Barsinghausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barsinghausen
Context triple: [Mont-Saint-Aignan, hasTwinTown, Barsinghausen]
  • A. Barsinghausen chosen
    Barsinghausen is a town in Lower Saxony, Germany, located near Hanover and known historically for its mining industry and proximity to the Deister hills.
  • B. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • C. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • D. Ehringshausen
    Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
  • E. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda9009ce88190b77c8f02f38107e1 completed May 8, 2026, 9:12 a.m.
Created at: April 9, 2026, 9:35 p.m.