Triple
T14644661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ujae Airport |
E343814
|
entity |
| Predicate | hasLimitedFacilities |
P115196
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ujae Airport, hasLimitedFacilities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLimitedFacilities Context triple: [Ujae Airport, hasLimitedFacilities, true]
-
A.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
B.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
C.
hasMaintenanceFacilities
Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
-
D.
hasGoodsFacilities
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
-
E.
hasAblutionFacilities
Indicates that an entity provides or is equipped with facilities for performing ablution or ritual washing.
- F. None of above. chosen
Provenance (4 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ea6d8481908e6331ca173c646b |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:26 a.m.