Triple
T401102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hajj Terminal, King Abdulaziz International Airport |
E9282
|
entity |
| Predicate | numberOfTents |
P12992
|
FINISHED |
| Object | 210 |
—
|
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: 210 | Statement: [Hajj Terminal, King Abdulaziz International Airport, numberOfTents, 210]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTents Context triple: [Hajj Terminal, King Abdulaziz International Airport, numberOfTents, 210]
-
A.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
B.
numberOfTanks
Indicates the quantity or count of tanks associated with a given entity or context.
-
C.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
-
D.
numberOfTubes
Indicates the quantity of tubes associated with or contained by a given entity.
-
E.
numberOfDomes
Indicates the quantity of domes that an entity possesses or is associated with.
- 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.