Triple

T6211105
Position Surface form Disambiguated ID Type / Status
Subject CDG Terminal 2 E138870 entity
Predicate hasPart P35 FINISHED
Object Terminal 2G E99006 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: Terminal 2G | Statement: [CDG Terminal 2, hasPart, Terminal 2G]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2G
Context triple: [CDG Terminal 2, hasPart, Terminal 2G]
  • A. Terminal 2G chosen
    Terminal 2G is a regional satellite terminal at Paris Charles de Gaulle Airport primarily serving short-haul European flights operated by Air France and its partners.
  • B. Terminal 2D
    Terminal 2D is a passenger terminal at Paris Charles de Gaulle Airport, serving as one of the facilities handling flights and travelers at this major international hub.
  • C. Terminal 2
    Terminal 2 is a modern, sustainably designed passenger terminal at San Francisco International Airport known for its upgraded amenities, art installations, and improved traveler experience.
  • D. Terminal 2
    Terminal 2 is a modern passenger terminal at Dublin Airport that primarily serves major international and transatlantic flights.
  • E. Terminal 2
    Terminal 2 is the modern international passenger terminal at Nội Bài International Airport in Hanoi, Vietnam, serving most of the airport’s international 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062896f3881909f264bb45badc5d0 completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f57821c8190bd7a5f6bf286ab09 completed March 23, 2026, 4:50 p.m.
Created at: March 22, 2026, 4:21 p.m.