Triple

T8797536
Position Surface form Disambiguated ID Type / Status
Subject Glashütten E209325 entity
Predicate locatedNear P294 FINISHED
Object Bad Camberg E209324 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 Camberg | Statement: [Glashütten, locatedNear, Bad Camberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Camberg
Context triple: [Glashütten, locatedNear, Bad Camberg]
  • A. Bad Camberg chosen
    Bad Camberg is a German spa town in the state of Hesse, known for its historic half-timbered old town and therapeutic health resorts.
  • B. Bad Brambach
    Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
  • C. Bad Mergentheim
    Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
  • D. Bad Tennstedt
    Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
  • E. Bad Nauheim
    Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa370d08190885ef65e3a3e56d3 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f5d655881909013ac3e2ac0cebb completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:44 p.m.