Triple

T3381773
Position Surface form Disambiguated ID Type / Status
Subject Air Berlin E71201 entity
Predicate operatedFromAirport P31126 FINISHED
Object Düsseldorf Airport E195585 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 Airport | Statement: [Air Berlin, operatedFromAirport, Düsseldorf Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Düsseldorf Airport
Context triple: [Air Berlin, operatedFromAirport, Düsseldorf Airport]
  • A. Düsseldorf Airport chosen
    Düsseldorf Airport is a major international airport in western Germany serving the city of Düsseldorf and the surrounding Rhine-Ruhr metropolitan region.
  • B. Cologne Bonn Airport
    Cologne Bonn Airport is a major international airport in western Germany serving the cities of Cologne and Bonn and acting as an important passenger and cargo hub.
  • C. Frankfurt Airport
    Frankfurt Airport is one of Europe’s busiest international aviation hubs, serving as a major global gateway and primary airport for the city of Frankfurt am Main in Germany.
  • D. Hannover Airport
    Hannover Airport is an international airport serving the city of Hanover in northern Germany, handling passenger and cargo flights for the region.
  • E. Hamburg Airport
    Hamburg Airport is an international airport in northern Germany serving the city of Hamburg and the surrounding region as a major passenger and cargo hub.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5e9af608190bfb228ef99a87bb7 completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3344f9b448190aab1038ead60fa48 completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:14 p.m.