Triple

T22220316
Position Surface form Disambiguated ID Type / Status
Subject Franz von Lenbach E549191 entity
Predicate placeOfBirth P1 FINISHED
Object Schrobenhausen 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: Schrobenhausen | Statement: [Franz von Lenbach, placeOfBirth, Schrobenhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schrobenhausen
Context triple: [Franz von Lenbach, placeOfBirth, Schrobenhausen]
  • A. Neuburg-Schrobenhausen chosen
    Neuburg-Schrobenhausen is a rural district in the Bavarian region of Upper Bavaria, Germany, known for its mix of historic towns and agricultural landscapes.
  • B. Schwanau
    Schwanau is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine River and the French border.
  • C. Ottmarsheim
    Ottmarsheim is a commune in northeastern France’s Alsace region, known for its historic Romanesque church and location along the Rhine.
  • D. Gerlachsheim
    Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
  • E. Grafenhausen
    Grafenhausen is a municipality in the Waldshut district of Baden-Württemberg in southwestern Germany, known for its Black Forest setting and traditional rural character.
  • 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_69e11e403d6481909a94d0aaf157f6ef completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b8fa3d081908db0a0556b009d8f completed April 28, 2026, 9:50 p.m.
Created at: April 16, 2026, 8:37 p.m.