Triple

T14601187
Position Surface form Disambiguated ID Type / Status
Subject Terminal 2 complex E342707 entity
Predicate hasPart P35 FINISHED
Object Terminal 2D E65653 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 2D | Statement: [Terminal 2 complex, hasPart, Terminal 2D]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2D
Context triple: [Terminal 2 complex, hasPart, Terminal 2D]
  • A. Terminal 2D chosen
    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.
  • B. Terminal 3D
    Terminal 3D is a concourse of Beijing Capital International Airport’s expansive Terminal 3 complex, serving as one of its dedicated passenger boarding and arrival areas.
  • C. Terminal 1D
    Terminal 1D is a domestic passenger terminal at Indira Gandhi International Airport in Delhi, India, serving primarily low-cost and short-haul flights.
  • D. Terminal 1D
    Terminal 1D is a passenger terminal at Jomo Kenyatta International Airport in Nairobi, Kenya, serving regional and international flights with check-in, boarding, and arrival facilities.
  • E. Terminal C (former)
    Terminal C (former) was a now-closed passenger terminal at Kansas City International Airport that once served as one of its primary concourses for airline operations.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb438748081908020ce04b869866a completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94cc9fbc819090ae4efe9bc618aa completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.