Triple

T10950868
Position Surface form Disambiguated ID Type / Status
Subject Condor E258721 entity
Predicate focusCity P164 FINISHED
Object Hanover Airport E118889 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: Hanover Airport | Statement: [Condor, focusCity, Hanover Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover Airport
Context triple: [Condor, focusCity, Hanover Airport]
  • A. Hannover Airport chosen
    Hannover Airport is an international airport serving the city of Hanover in northern Germany, handling passenger and cargo flights for the region.
  • 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. 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.
  • D. 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.
  • E. Berlin Schönefeld Airport
    Berlin Schönefeld Airport was Berlin’s former secondary international airport located southeast of the city, which was eventually incorporated into the new Berlin Brandenburg Airport complex.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770fc156c8190826e124c13ce7242 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e5099f57ac81909e7734b83ad96a40 completed April 19, 2026, 4:58 p.m.
Created at: April 8, 2026, 9:23 p.m.