Triple
T25430870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportInfrastructureLevel |
P135806
|
FINISHED |
| Object | basic facilities |
—
|
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: basic facilities | Statement: [FUN, airportInfrastructureLevel, basic facilities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportInfrastructureLevel Context triple: [FUN, airportInfrastructureLevel, basic facilities]
-
A.
hasAirportClassification
Indicates that an airport is assigned a specific classification or category based on defined criteria.
-
B.
airportFeature
chosen
Indicates that an airport possesses or is characterized by a particular feature, facility, or attribute.
-
C.
airportDesignation
Indicates that an entity is officially designated or classified as an airport.
-
D.
isToweredAirport
Indicates that an airport is equipped with and operates an active air traffic control tower.
-
E.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 1:58 p.m.