Triple

T9434295
Position Surface form Disambiguated ID Type / Status
Subject Herford E227462 entity
Predicate locatedNear P294 FINISHED
Object Bad Oeynhausen E387270 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: Bad Oeynhausen | Statement: [Herford, locatedNear, Bad Oeynhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Oeynhausen
Context triple: [Herford, locatedNear, Bad Oeynhausen]
  • A. Bad Oeynhausen chosen
    Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
  • B. Bad Rothenfelde
    Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
  • C. Bad Honnef
    Bad Honnef is a spa town on the Rhine in North Rhine-Westphalia, Germany, known for its scenic setting near the Siebengebirge hills and its historical associations with prominent political figures.
  • D. Bad Eilsen
    Bad Eilsen is a spa town in Lower Saxony, Germany, historically notable for serving as the post–World War II headquarters of the Royal Air Force’s British Air Forces of Occupation.
  • E. Bad Säckingen
    Bad Säckingen is a historic spa town in southwestern Germany on the Rhine River, known for its medieval old town and one of the longest covered wooden bridges in Europe.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e62d53c81908055e0967e6cd54d completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1104a002481909ca805893bac61c6 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:49 p.m.