Triple

T757788
Position Surface form Disambiguated ID Type / Status
Subject Nuremberg U-Bahn E15595 entity
Predicate hasTerminus P388 FINISHED
Object Flughafen Nürnberg E84051 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: Flughafen Nürnberg | Statement: [Nuremberg U-Bahn, hasTerminus, Flughafen Nürnberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flughafen Nürnberg
Context triple: [Nuremberg U-Bahn, hasTerminus, Flughafen Nürnberg]
  • A. Nuremberg Airport chosen
    Nuremberg Airport is an international airport in northern Bavaria, Germany, serving the city of Nuremberg and the surrounding Franconia region with passenger and cargo flights.
  • B. 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.
  • C. Berlin Brandenburg Airport
    Berlin Brandenburg Airport is the main international airport serving Germany’s capital region, designed to replace and consolidate Berlin’s former commercial airports.
  • D. Tempelhof Airport
    Tempelhof Airport is a historic Berlin airfield best known as a central hub of the Berlin Airlift during the Cold War.
  • E. Vienna International Airport
    Vienna International Airport is Austria’s largest and busiest airport, serving as the primary international gateway to Vienna and a major hub for Central and Eastern Europe.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66c2e108190a754c60d2eac6676 completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a673345f18819084e2caf380e46b30 completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:37 p.m.