Triple

T2764484
Position Surface form Disambiguated ID Type / Status
Subject LaGuardia Airport E61301 entity
Predicate hasTerminal P182 FINISHED
Object Terminal D E61750 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 D | Statement: [LaGuardia Airport, hasTerminal, Terminal D]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Terminal D
Context triple: [LaGuardia Airport, hasTerminal, Terminal D]
  • A. Terminal D
    Terminal D is one of the passenger terminals at Luis Muñoz Marín International Airport in Puerto Rico, serving commercial air travelers with check-in, security, boarding gates, and related airport services.
  • B. Terminal D
    Terminal D is one of the main passenger terminals at Sheremetyevo International Airport in Moscow, serving numerous international and domestic flights.
  • C. Terminal D
    Terminal D is the international terminal at Dallas/Fort Worth International Airport, serving as a major hub for long-haul and global flights with extensive passenger amenities.
  • D. Terminal D
    Terminal D is one of the passenger terminals at Philadelphia International Airport, serving domestic flights with various airlines and amenities.
  • E. Terminal D chosen
    Terminal D is one of the passenger terminals at New York City's LaGuardia Airport, serving as a concourse for airline check-in, security, boarding, and arrivals.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd541c2c8190a983a6f6a0b24ed9 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc04630b8819081cd8ddac1d42184 completed March 10, 2026, 6:55 a.m.
Created at: March 6, 2026, 9:57 p.m.