Triple

T6872794
Position Surface form Disambiguated ID Type / Status
Subject Nassau, Germany E158592 entity
Predicate locatedNear P294 FINISHED
Object Bad Ems E317369 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 Ems | Statement: [Nassau, Germany, locatedNear, Bad Ems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Ems
Context triple: [Nassau, Germany, locatedNear, Bad Ems]
  • A. Bad Ems chosen
    Bad Ems is a historic spa town in western Germany, renowned for its mineral springs and picturesque location along the Lahn River.
  • B. 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.
  • C. Bad Tölz
    Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
  • D. Bad Harzburg
    Bad Harzburg is a German spa and resort town on the northern edge of the Harz Mountains, known for its thermal baths, hiking trails, and historic castle ruins.
  • E. Bad Pyrmont
    Bad Pyrmont is a German spa town in Lower Saxony renowned for its mineral springs, historic Kurpark, and long tradition as a health resort.
  • 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_69c68832af1481908ce356e133ebaebe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8c73ea08190b6bb1463e7ead47b completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742af0df88190bb23b7495c279e08 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.