Triple

T11522803
Position Surface form Disambiguated ID Type / Status
Subject Günzburg E273207 entity
Predicate hasTwinTown P919 FINISHED
Object Sonnenbühl E790132 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: Sonnenbühl | Statement: [Günzburg, hasTwinTown, Sonnenbühl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sonnenbühl
Context triple: [Günzburg, hasTwinTown, Sonnenbühl]
  • A. Sonnenbühl chosen
    Sonnenbühl is a municipality in the Swabian Alb region of Baden-Württemberg, Germany, known for its karst landscapes, caves, and outdoor recreation.
  • B. Meisenbühl
    Meisenbühl is a locality or neighborhood that forms part of the municipality of Oberkirch.
  • C. Münchberg
    Münchberg is a town in the Upper Franconia region of Bavaria, Germany, known historically for its textile industry and as a local commercial center.
  • D. Teutschenthal
    Teutschenthal is a municipality in the Saalekreis district of Saxony-Anhalt in central Germany.
  • E. Böhlen
    Böhlen is a small town in the Leipzig district of Saxony, Germany, known for its lignite mining and power generation industries.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d87fd26648819083de19bcddf8ad69 completed April 10, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6af38e3548190a5192894932d9b1d completed May 3, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:37 p.m.