Triple

T5208321
Position Surface form Disambiguated ID Type / Status
Subject Munich Airport E117566 entity
Predicate operator P179 FINISHED
Object Flughafen München GmbH E117566 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 München GmbH | Statement: [Munich Airport, operator, Flughafen München GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flughafen München GmbH
Context triple: [Munich Airport, operator, Flughafen München GmbH]
  • A. Berliner Flughafen-Gesellschaft
    Berliner Flughafen-Gesellschaft was the municipal company responsible for operating Berlin’s airports, notably during the Cold War era.
  • B. Flughafen Berlin Brandenburg GmbH
    Flughafen Berlin Brandenburg GmbH is the state-owned company responsible for owning, managing, and developing Berlin’s airport infrastructure, including Berlin Brandenburg Airport.
  • C. Munich Airport chosen
    Munich Airport is a major international aviation hub in Bavaria, Germany, serving as one of the country’s busiest airports and a key base for Lufthansa.
  • D. Flughafen Wien AG
    Flughafen Wien AG is an Austrian publicly listed company that operates and manages Vienna International Airport and related airport services.
  • E. Nuremberg Airport
    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.
  • 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_69bd4463dd3c81909966123f20b79d57 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a6d70d081908c74e86b3bca9ba2 completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefd4b75c8190b1b87b8d93925245 completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:47 p.m.