Triple

T17550567
Position Surface form Disambiguated ID Type / Status
Subject Montecatini Terme E427449 entity
Predicate twinnedWith P1072 FINISHED
Object Bad Kissingen NE NERFINISHED

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 Kissingen | Statement: [Montecatini Terme, twinnedWith, Bad Kissingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Kissingen
Context triple: [Montecatini Terme, twinnedWith, Bad Kissingen]
  • A. Bad Kissingen chosen
    Bad Kissingen is a historic spa town in northern Bavaria, Germany, renowned for its mineral springs and 19th-century wellness resorts.
  • B. Gauting
    Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
  • C. Backnang
    Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
  • D. Ingolstadt
    Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
  • E. Germering
    Germering is a town in Upper Bavaria, Germany, located just west of Munich and known as a residential and commuter suburb of the Munich metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e454656dc08190bba85b93bd07b0a2 completed April 19, 2026, 4:04 a.m.
Created at: April 10, 2026, 5:50 a.m.