Triple
T16061488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Nanyuan Airport |
E389622
|
entity |
| Predicate | hadPassengerServicesUntil |
P4906
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [Beijing Nanyuan Airport, hadPassengerServicesUntil, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPassengerServicesUntil Context triple: [Beijing Nanyuan Airport, hadPassengerServicesUntil, 2019]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
C.
formerPassengerService
chosen
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
D.
openedAsPassengerService
Indicates that a transportation facility or route began operating specifically for carrying passengers.
-
E.
operatedPassengerServices
Indicates that an entity provided and managed transportation services specifically for carrying passengers.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:57 a.m.