Triple

T19500240
Position Surface form Disambiguated ID Type / Status
Subject Bacolod–Silay Airport E487882 entity
Predicate servesAirline P12356 FINISHED
Object Philippine Airlines NE NERFINISHED

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: Philippine Airlines | Statement: [Bacolod–Silay Airport, servesAirline, Philippine Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippine Airlines
Context triple: [Bacolod–Silay Airport, servesAirline, Philippine Airlines]
  • A. Philippine Airlines chosen
    Philippine Airlines is the flag carrier of the Philippines, operating a wide network of domestic and international flights across Asia, North America, Oceania, and beyond.
  • B. Cebu Pacific
    Cebu Pacific is a major low-cost airline based in the Philippines, known for operating extensive domestic and regional routes across Asia.
  • C. Royal Air Philippines
    Royal Air Philippines is a Philippine low-cost airline operating domestic and regional flights, primarily based in Manila.
  • D. Dragonair
    Dragonair was a Hong Kong-based regional airline, later rebranded as Cathay Dragon, that primarily operated flights within Asia.
  • E. PAL Airlines
    PAL Airlines is a Canadian regional airline that operates passenger and cargo flights primarily throughout Newfoundland and Labrador and other parts of eastern Canada.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6350ce7cc819086d77bbd9cd52b53 completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.