Triple
T34818672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | เขตดอนเมือง |
E1003705
|
entity |
| Predicate | hasPrimaryAirportTrafficType |
P27830
|
FINISHED |
| Object | เที่ยวบินภายในประเทศ |
—
|
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: เที่ยวบินภายในประเทศ | Statement: [เขตดอนเมือง, hasPrimaryAirportTrafficType, เที่ยวบินภายในประเทศ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryAirportTrafficType Context triple: [เขตดอนเมือง, hasPrimaryAirportTrafficType, เที่ยวบินภายในประเทศ]
-
A.
hasPrimaryAirportRole
Indicates that an entity holds the main or principal functional role associated with an airport.
-
B.
isToweredAirport
Indicates that an airport is equipped with and operates an active air traffic control tower.
-
C.
hasCargoTrafficType
Indicates that an entity is associated with a specific type or category of cargo traffic it handles or supports.
-
D.
servesPassengerTrafficType
chosen
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
E.
isMajorCargoAirport
Indicates that an airport primarily handles large volumes of cargo traffic and serves as a significant freight hub.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a0326d40cb88190802f61fa832f8ca8 |
completed | May 12, 2026, 1:10 p.m. |
| PD | Predicate disambiguation | batch_6a03268b4f9c8190b3e135b37ed373c3 |
completed | May 12, 2026, 1:09 p.m. |
Created at: May 3, 2026, 4 p.m.