Triple

T6625868
Position Surface form Disambiguated ID Type / Status
Subject Menden E149798 entity
Predicate locatedNear P294 FINISHED
Object Fröndenberg E456760 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: Fröndenberg | Statement: [Menden, locatedNear, Fröndenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fröndenberg
Context triple: [Menden, locatedNear, Fröndenberg]
  • A. Fröndenberg chosen
    Fröndenberg is a small town in North Rhine-Westphalia, Germany, situated on the Ruhr River and known for its scenic rural surroundings.
  • B. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • C. Pfullendorf
    Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
  • D. Rhöndorf
    Rhöndorf is a district of Bad Honnef in Germany, best known as the longtime residence and final home of the first Chancellor of the Federal Republic of Germany, Konrad Adenauer.
  • E. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af8187d881908b7a86f2cae5de23 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eeeaa67881908bef71c5fa61c599 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:58 p.m.