Triple

T16479888
Position Surface form Disambiguated ID Type / Status
Subject Schluchseewerk AG E400286 entity
Predicate headquartersLocation P62 FINISHED
Object Laufenburg E540418 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: Laufenburg | Statement: [Schluchseewerk AG, headquartersLocation, Laufenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laufenburg
Context triple: [Schluchseewerk AG, headquartersLocation, Laufenburg]
  • A. Laufenburg chosen
    Laufenburg is a historic town on the Rhine River, straddling the border between Switzerland and Germany and known for its medieval architecture and river scenery.
  • B. Lauffeld
    Lauffeld is a village in present-day Belgium best known as the site of the 1747 Battle of Lauffeld during the War of the Austrian Succession.
  • C. Roggenburg
    Roggenburg is a small municipality in the Bavarian district of Neu-Ulm in southern Germany, known for its historic Premonstratensian monastery and rural setting.
  • D. Friedlingen
    Friedlingen is a district of the German town Weil am Rhein, located in the far southwest of Baden-Württemberg near the borders with France and Switzerland.
  • E. Bendorf
    Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e01f6c88190b75a0d6c94786426 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f60ea8881908f073a28c407a1f4 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:13 a.m.