Triple
T401118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hajj Terminal, King Abdulaziz International Airport |
E9282
|
entity |
| Predicate | coolingStrategy |
P12994
|
FINISHED |
| Object | passive cooling through shade and airflow |
—
|
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: passive cooling through shade and airflow | Statement: [Hajj Terminal, King Abdulaziz International Airport, coolingStrategy, passive cooling through shade and airflow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coolingStrategy Context triple: [Hajj Terminal, King Abdulaziz International Airport, coolingStrategy, passive cooling through shade and airflow]
-
A.
coolant
Indicates that one entity functions as a coolant for another, serving to absorb and remove heat from it.
-
B.
operatingTemperature
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
C.
isCryogenic
Indicates that something operates at, is designed for, or involves extremely low (cryogenic) temperatures.
-
D.
reactorType
Indicates the specific kind or category of reactor associated with an entity.
-
E.
hasColdPhase
Indicates that an entity undergoes or includes a period or stage characterized by low temperature or cold conditions.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec9f77888190bcc2bc68d201ed35 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96ee4ec8190a5c0e3f491d3963d |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.