Triple

T20811253
Position Surface form Disambiguated ID Type / Status
Subject Ettlingen E512308 entity
Predicate hasSubdivision P747 FINISHED
Object Schöllbronn E897583 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: Schöllbronn | Statement: [Ettlingen, hasSubdivision, Schöllbronn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schöllbronn
Context triple: [Ettlingen, hasSubdivision, Schöllbronn]
  • A. Waldbronn chosen
    Waldbronn is a municipality in the state of Baden-Württemberg in southwestern Germany, known for its spa facilities and proximity to the city of Karlsruhe.
  • B. Schorndorf
    Schorndorf is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and as the birthplace of automotive pioneer Gottlieb Daimler.
  • C. Baiersbronn
    Baiersbronn is a municipality in Germany’s Black Forest renowned for its scenic landscapes and high concentration of Michelin-starred restaurants.
  • D. Winnenden
    Winnenden is a small town in the German state of Baden-Württemberg, known for its historic center and role in regional Protestant history.
  • E. Bromskirchen
    Bromskirchen is a small municipality in the Waldeck-Frankenberg district of Hesse, Germany, near the border with North Rhine-Westphalia.
  • 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_69e0b4cd25088190b48ca9700cd24efc completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2d338ac819096d4a33de831609e completed April 21, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a08f8cb61388190922a898ee4c44d2e completed May 16, 2026, 11:07 p.m.
Created at: April 16, 2026, 12:40 p.m.