Triple
T25003163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Abdulaziz International Airport |
E625770
|
entity |
| Predicate | hasHajjFacilities |
P12416
|
FINISHED |
| Object | dedicated Hajj terminal complex |
—
|
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: dedicated Hajj terminal complex | Statement: [King Abdulaziz International Airport, hasHajjFacilities, dedicated Hajj terminal complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHajjFacilities Context triple: [King Abdulaziz International Airport, hasHajjFacilities, dedicated Hajj terminal complex]
-
A.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
B.
hasMinaretFeature
Indicates that something possesses or includes a minaret as one of its architectural or structural features.
-
C.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
D.
hasGoodsFacilities
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
-
E.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44b0d1ed48190bcde75a65c8f86a0 |
completed | May 1, 2026, 6:41 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:05 a.m.