Triple
T36943290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cebu–Davao |
E913833
|
entity |
| Predicate | primaryAirportAtDestination |
P166945
|
FINISHED |
| Object | Francisco Bangoy International Airport |
E460598
|
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: Francisco Bangoy International Airport | Statement: [Cebu–Davao, primaryAirportAtDestination, Francisco Bangoy International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAirportAtDestination Context triple: [Cebu–Davao, primaryAirportAtDestination, Francisco Bangoy International Airport]
-
A.
parentAirport
Indicates that one airport serves as the primary or overarching facility from which another, subsidiary or associated airport is derived or managed.
-
B.
previousPrimaryAirportFor
Indicates that one airport was formerly the main or primary airport serving a particular location or entity before being replaced by another.
-
C.
typicalDestinationAirportIATA
Indicates the IATA airport code that is typically the destination in this kind of trip or route.
-
D.
destinationAirportRole
Indicates the role an airport plays as the destination point within a given travel, flight, or route relationship.
-
E.
destinationAirportName
chosen
Indicates the name of the airport that serves as the destination in a travel or flight-related relationship.
- F. None of above.
Provenance (4 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a402b94fd208190ac2e50cf168b4617 |
completed | June 27, 2026, 7:59 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.