Triple

T16886385
Position Surface form Disambiguated ID Type / Status
Subject Igersheim E421550 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Weikersheim 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: Weikersheim | Statement: [Igersheim, hasNeighbouringMunicipality, Weikersheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weikersheim
Context triple: [Igersheim, hasNeighbouringMunicipality, Weikersheim]
  • A. Weikersheim chosen
    Weikersheim is a small historic town in the Tauber Valley of Baden-Württemberg, Germany, known for its Renaissance castle and well-preserved old town.
  • B. Weinheim
    Weinheim is a historic town in southwestern Germany, known for its picturesque old town, twin castles, and location on the Bergstraße at the edge of the Odenwald.
  • C. Bensheim
    Bensheim is a historic town in southern Hesse, Germany, known for its wine-growing tradition and picturesque location on the Bergstraße at the edge of the Odenwald.
  • D. Wehrheim
    Wehrheim is a small municipality in the Hochtaunus district of Hesse, Germany, known for its rural character and proximity to the Taunus mountain range.
  • E. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc126e881909dae8133ad34acc9 completed April 18, 2026, 5:13 p.m.
Created at: April 10, 2026, 5:29 a.m.