Triple

T12429672
Position Surface form Disambiguated ID Type / Status
Subject Edmund Veesenmayer E296993 entity
Predicate placeOfBirth P1 FINISHED
Object Bad Kissingen E567840 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 Kissingen | Statement: [Edmund Veesenmayer, placeOfBirth, Bad Kissingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Kissingen
Context triple: [Edmund Veesenmayer, placeOfBirth, 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 (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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d7ddc688190bddb242d67fa6e89 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f70928c8190a872ecb47b8da2c7 completed May 3, 2026, 5:01 p.m.
Created at: April 8, 2026, 9:55 p.m.