Triple

T36655256
Position Surface form Disambiguated ID Type / Status
Subject Terminal 4 (Ninoy Aquino International Airport) E904969 entity
Predicate internationalFlightsHandled P115937 FINISHED
Object limited or none 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: limited or none | Statement: [Terminal 4 (Ninoy Aquino International Airport), internationalFlightsHandled, limited or none]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: internationalFlightsHandled
Context triple: [Terminal 4 (Ninoy Aquino International Airport), internationalFlightsHandled, limited or none]
  • A. hasInternationalFlights
    Indicates that an airport or airline operates flights connecting to destinations in other countries.
  • B. hasInternationalDestinations
    Indicates that an entity offers, includes, or is connected to destinations located in foreign countries.
  • C. hasInternationalTerminal
    Indicates that a transportation facility includes a terminal specifically designated for handling international arrivals and departures.
  • D. handlesInternationalTrafficAt chosen
    Indicates that an entity manages or processes international traffic at a specified location or facility.
  • E. quantityFlown
    Indicates the amount or volume that has been transported by flying from one place to another.
  • 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_69f76e6e3b908190970251b30f76ad71 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69feaa483fcc81909d8a46b38a8717bf completed May 9, 2026, 3:30 a.m.
PD Predicate disambiguation batch_69fea8c9d45c81908ccc8619e5fefac1 completed May 9, 2026, 3:23 a.m.
Created at: May 3, 2026, 4:11 p.m.