Triple

T20643152
Position Surface form Disambiguated ID Type / Status
Subject Hannover Airport E507280 entity
Predicate hasTerminal P182 FINISHED
Object Terminal C NE NERFINISHED

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: Terminal C | Statement: [Hannover Airport, hasTerminal, Terminal C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal C
Context triple: [Hannover Airport, hasTerminal, Terminal C]
  • A. Terminal C
    Terminal C is one of the main passenger terminals at Boston Logan International Airport, serving numerous domestic and some international flights with a variety of airlines and amenities.
  • B. Terminal C
    Terminal C is a modern passenger terminal at Orlando International Airport designed to handle increased domestic and international air traffic with updated amenities and infrastructure.
  • C. Terminal C
    Terminal C is one of the passenger terminals at Ministro Pistarini International Airport (Ezeiza), serving as a key facility for airline operations and traveler services.
  • D. Terminal C chosen
    Terminal C is one of the passenger terminals at Hannover Airport in Germany, serving commercial air traffic with check-in, security, and boarding facilities.
  • E. Terminal C
    Terminal C is a passenger terminal at Katowice Airport in Poland, serving as one of the airport’s main facilities for handling air travelers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1c51f48190abba54a5aace9fc8 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.