Triple

T11044049
Position Surface form Disambiguated ID Type / Status
Subject Terminal 2 (Hamburg Airport) E261093 entity
Predicate partOf P40 FINISHED
Object Hamburg Airport E44344 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: Hamburg Airport | Statement: [Terminal 2 (Hamburg Airport), partOf, Hamburg Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg Airport
Context triple: [Terminal 2 (Hamburg Airport), partOf, Hamburg Airport]
  • A. Hamburg Airport chosen
    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.
  • B. Hannover Airport
    Hannover Airport is an international airport serving the city of Hanover in northern Germany, handling passenger and cargo flights for the region.
  • 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. Bremen Airport
    Bremen Airport is an international airport in northern Germany serving the city of Bremen and the surrounding region with domestic and European flights.
  • E. Munich Airport
    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.
  • 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7982e08548190aec04099cef9453c completed April 9, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b76fa8348190bb42f1c71eb0e545 completed April 20, 2026, 5:19 a.m.
Created at: April 8, 2026, 9:26 p.m.