Triple
T21098553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laredo International Airport |
E519831
|
entity |
| Predicate | supportsCommercialAirlines |
P80333
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Laredo International Airport, supportsCommercialAirlines, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCommercialAirlines Context triple: [Laredo International Airport, supportsCommercialAirlines, yes]
-
A.
supportsCommercialFlights
chosen
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
-
B.
supportsCharterFlights
Indicates that one entity provides the capability or service of operating or accommodating charter flights for another entity.
-
C.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
D.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
E.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b5b51608190aa286d89a9d54e9f |
completed | April 21, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:52 p.m.