Triple

T21380592
Position Surface form Disambiguated ID Type / Status
Subject Schwanau E527341 entity
Predicate hasSubdivision P747 FINISHED
Object Allmannsweier 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: Allmannsweier | Statement: [Schwanau, hasSubdivision, Allmannsweier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allmannsweier
Context triple: [Schwanau, hasSubdivision, Allmannsweier]
  • A. Allmannsweier chosen
    Allmannsweier is a village in the Ortenau district of Baden-Württemberg, Germany, now incorporated into the municipality of Schwanau.
  • B. Adelsried
    Adelsried is a small municipality in the Swabian region of Bavaria in southern Germany.
  • C. Lorsbach
    Lorsbach is a district of the town Hofheim am Taunus in the German state of Hesse, situated in the Taunus mountain region.
  • D. Grafenried
    Grafenried is a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
  • E. Ötigheim
    Ötigheim is a small municipality in southwestern Germany’s Baden-Württemberg state, known for its open-air theater and rural character within the Rastatt district.
  • 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0cdab8c8190a7eebe6e5961ee75 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:11 p.m.