Triple

T10869667
Position Surface form Disambiguated ID Type / Status
Subject Andreas Osiander E256617 entity
Predicate birthPlace P1 FINISHED
Object Günzenhausen E118611 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: Günzenhausen | Statement: [Andreas Osiander, birthPlace, Günzenhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Günzenhausen
Context triple: [Andreas Osiander, birthPlace, Günzenhausen]
  • A. Gunzenhausen chosen
    Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
  • B. Gräfenhausen
    Gräfenhausen is a district of the town of Weiterstadt in the state of Hesse, Germany.
  • C. Gelnhausen
    Gelnhausen is a historic town in the German state of Hesse, known for its well-preserved medieval architecture and former status as a Free Imperial City of the Holy Roman Empire.
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Herzogenaurach
    Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75170665881909944f92c2cdbe7e6 completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69f61e2fa3bc81909edef00c61265c55 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:20 p.m.