Triple

T12566940
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Oerlinghausen E710785 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: Oerlinghausen | Statement: [Province of Westphalia, containsSettlement, Oerlinghausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oerlinghausen
Context triple: [Province of Westphalia, containsSettlement, Oerlinghausen]
  • A. Oerlinghausen chosen
    Oerlinghausen is a small town in the German state of North Rhine-Westphalia, known for its scenic Teutoburg Forest surroundings and historical roots.
  • B. Sprockhövel
    Sprockhövel is a small town in North Rhine-Westphalia, Germany, known for its historical coal mining heritage and location in the hilly Ruhr region.
  • C. Ehringshausen
    Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
  • D. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • E. Sondershausen
    Sondershausen is a small town in the German state of Thuringia, known for its historic castle, former role as a princely residence, and long tradition of mining and music.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a325948190994bcfc9d571a3a8 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb63c80048190be87b41cdd4ac775 completed May 7, 2026, 3:56 p.m.
Created at: April 8, 2026, 11:49 p.m.