Triple

T3147221
Position Surface form Disambiguated ID Type / Status
Subject International Paralympic Committee E65792 entity
Predicate foundedIn P41 FINISHED
Object Düsseldorf E36993 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: Düsseldorf | Statement: [International Paralympic Committee, foundedIn, Düsseldorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Düsseldorf
Context triple: [International Paralympic Committee, foundedIn, Düsseldorf]
  • A. Düsseldorf chosen
    Düsseldorf is a major German city on the Rhine River known for its fashion and art scenes, modern architecture, and status as an important economic and financial center.
  • B. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • C. Duisburg
    Duisburg is a major industrial and port city in western Germany’s Ruhr region, known for its steel production and one of the world’s largest inland harbors.
  • D. Krefeld
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • E. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada598ccf08190b8817c456f38f2d7 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf88d99da08190996996079b947498 completed March 22, 2026, 6:14 a.m.
Created at: March 8, 2026, 3:05 p.m.