Triple

T21927570
Position Surface form Disambiguated ID Type / Status
Subject Franz Sigel E541480 entity
Predicate placeOfBirth P1 FINISHED
Object Sinsheim 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: Sinsheim | Statement: [Franz Sigel, placeOfBirth, Sinsheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinsheim
Context triple: [Franz Sigel, placeOfBirth, Sinsheim]
  • A. Sinsheim chosen
    Sinsheim is a town in southwestern Germany’s Rhine-Neckar region, known for its automotive and technology museum featuring historic cars, aircraft, and other exhibits.
  • B. Kornwestheim
    Kornwestheim is a mid-sized town in the German state of Baden-Württemberg, located just north of Stuttgart and known for its industrial heritage and residential character.
  • C. Riedheim
    Riedheim is a village-level subdivision of the municipality of Hilzingen in the district of Konstanz, Baden-Württemberg, Germany.
  • D. Meerbusch
    Meerbusch is a town in the German state of North Rhine-Westphalia, situated on the west bank of the Rhine near Düsseldorf and known for its affluent residential areas and green surroundings.
  • E. Schriesheim
    Schriesheim is a historic town in southwestern Germany’s Rhine-Neckar region, known for its viticulture, picturesque old town, and location along the Bergstraße scenic route.
  • 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_69e0c47d74488190a15119108794a307 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f123fc188481909c74fd5f1bd52258 completed April 28, 2026, 9:17 p.m.
Created at: April 16, 2026, 7:46 p.m.