Triple
T20283100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tagbilaran Airport |
E503199
|
entity |
| Predicate | servedAsDestinationFor |
P50377
|
FINISHED |
| Object | PAL Express |
—
|
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: PAL Express | Statement: [Tagbilaran Airport, servedAsDestinationFor, PAL Express]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PAL Express Context triple: [Tagbilaran Airport, servedAsDestinationFor, PAL Express]
-
A.
PAL Express
chosen
PAL Express is a Philippine low-cost regional airline brand operating domestic and select international flights on behalf of Philippine Airlines.
-
B.
UP Express
UP Express is a dedicated airport rail link in Toronto that provides fast, frequent train service between Union Station downtown and Toronto Pearson International Airport.
-
C.
NAS EXPRESS
NAS EXPRESS is the airline callsign used by Flynas, a Saudi Arabian low-cost carrier.
-
D.
LAN Express
LAN Express was a Chilean regional airline operating domestic and short-haul routes as a subsidiary brand of LAN Airlines (now part of LATAM Airlines Group).
-
E.
Xpress
Xpress is a regional public transit service in Georgia that provides commuter bus connections between suburban areas and major employment centers.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6769049b48190bc449557b79b9e81 |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 10:40 a.m.