Triple

T13324698
Position Surface form Disambiguated ID Type / Status
Subject Blue Air E317407 entity
Predicate operatedDestination P50377 FINISHED
Object Cologne E35950 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: Cologne | Statement: [Blue Air, operatedDestination, Cologne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cologne
Context triple: [Blue Air, operatedDestination, Cologne]
  • A. Cologne chosen
    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.
  • B. Düsseldorf
    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.
  • C. Koblenz
    Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
  • D. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • E. Mannheim
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcd4cb008190af99c4856e76ac08 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f05b3e08190be0d4e0ad2bfb2d1 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9:30 p.m.