Triple
T1128315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David |
E24770
|
entity |
| Predicate | hasTransportFacilityType |
P2836
|
FINISHED |
| Object | international airport |
—
|
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: international airport | Statement: [David, hasTransportFacilityType, international airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportFacilityType Context triple: [David, hasTransportFacilityType, international airport]
-
A.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
B.
hasTransportHub
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
-
C.
hasTransportationSystem
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
-
D.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
E.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb48de2081909a0dce005b1c9df1 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.