Triple

T3381775
Position Surface form Disambiguated ID Type / Status
Subject Air Berlin E71201 entity
Predicate operatedFromAirport P31126 FINISHED
Object Munich Airport 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: Munich Airport | Statement: [Air Berlin, operatedFromAirport, Munich Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munich Airport
Context triple: [Air Berlin, operatedFromAirport, Munich Airport]
  • A. 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.
  • B. 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.
  • 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. 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.
  • E. Stuttgart Airport
    Stuttgart Airport is the international airport serving the city of Stuttgart in southwestern Germany, handling both passenger and cargo traffic for the region.
  • 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_69b34bc3f13c81909bec375bd080b7f3 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:14 p.m.