Triple

T12600299
Position Surface form Disambiguated ID Type / Status
Subject Bergisches Land E300838 entity
Predicate traversedByRiver P165 FINISHED
Object Dhünn E980419 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: Dhünn | Statement: [Bergisches Land, traversedByRiver, Dhünn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dhünn
Context triple: [Bergisches Land, traversedByRiver, Dhünn]
  • A. Dhünn chosen
    Dhünn is a river in North Rhine-Westphalia, Germany, that flows through the city of Leverkusen and serves as a tributary of the Wupper.
  • B. Zihl
    Zihl is a river in Switzerland that serves as a key tributary within the Aare river system.
  • C. Horgau
    Horgau is a small municipality in the Swabian region of Bavaria in southern Germany.
  • D. Hainichen
    Hainichen is a small town in the Free State of Saxony in eastern Germany, known for its historical architecture and location between the cities of Chemnitz and Dresden.
  • E. Todenfeld
    Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d1f6ac8190ab21ca7bcbc80129 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f66869c0b08190b13bcebbe354cd98 completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:09 p.m.