Triple

T325191
Position Surface form Disambiguated ID Type / Status
Subject KLAX E6499 entity
Predicate hasTerminal P182 FINISHED
Object Terminal 1 E13319 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 1 | Statement: [KLAX, hasTerminal, Terminal 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 1
Context triple: [KLAX, hasTerminal, Terminal 1]
  • A. Terminal 1 chosen
    Terminal 1 is one of the passenger terminals at Los Angeles International Airport, primarily serving domestic flights for several major U.S. airlines.
  • B. Terminal 1
    Terminal 1 is one of the main passenger terminals at Paris Charles de Gaulle Airport, known for its distinctive circular design and central location within the airport complex.
  • C. Terminal 1
    Terminal 1 is a passenger terminal at San Francisco International Airport that serves as one of the airport’s main facilities for airline check-in, security, and boarding.
  • D. Terminal 1
    Terminal 1 is one of the main passenger terminals at San Diego International Airport, serving various domestic airline operations and traveler amenities.
  • E. Terminal 1
    Terminal 1 is one of the passenger terminals at Raleigh–Durham International Airport, serving as a primary facility for airline check-in, security screening, and boarding.
  • 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_69a2e7933d6c8190bb2592ad13286ef2 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea959f9c819084602b8a1b5e66dd completed Feb. 28, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d241f924819087dedd32d7b6cc2b completed March 1, 2026, 5:44 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.