Triple

T16892507
Position Surface form Disambiguated ID Type / Status
Subject Terminal D of Philadelphia International Airport E424208 entity
Predicate hasCheckInCountersFor P24791 FINISHED
Object multiple U.S. domestic airlines LITERAL 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: multiple U.S. domestic airlines | Statement: [Terminal D of Philadelphia International Airport, hasCheckInCountersFor, multiple U.S. domestic airlines]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCheckInCountersFor
Context triple: [Terminal D of Philadelphia International Airport, hasCheckInCountersFor, multiple U.S. domestic airlines]
  • A. hasCheckInCounters chosen
    Indicates that an entity is associated with one or more check-in counters used for processing arrivals or registrations.
  • B. hasCheckoutCounter
    Indicates that one entity possesses or includes a checkout counter used for processing purchases or transactions.
  • C. hasCheckInSystem
    Indicates that an entity uses or is equipped with a system for registering or recording check-ins.
  • D. hasCounterService
    Indicates that a place provides service to customers over a counter, such as ordering, paying, or receiving items at a service counter.
  • E. hasCheckInCategory
    Indicates that an entity is associated with a specific category or type of check-in event.
  • F. None of above.

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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc5a5308190937ebd05356bd91d completed April 18, 2026, 5:13 p.m.
PD Predicate disambiguation batch_69e32b90ec3c819099c51bb7baf2984c completed April 18, 2026, 6:58 a.m.
Created at: April 10, 2026, 5:29 a.m.