Triple
T33659900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governorate of Saudi Arabia |
E862321
|
entity |
| Predicate | higherUnitCount |
P19248
|
FINISHED |
| Object | 13 provinces |
—
|
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: 13 provinces | Statement: [Governorate of Saudi Arabia, higherUnitCount, 13 provinces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherUnitCount Context triple: [Governorate of Saudi Arabia, higherUnitCount, 13 provinces]
-
A.
multipleUnit
Indicates that an entity is composed of or associated with more than one unit of the same type.
-
B.
higherDenomination
Indicates that one entity represents a monetary value that is greater than the monetary value represented by another entity.
-
C.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
D.
highDenomination
Indicates that something has a relatively large or high face value compared to other items in the same category (e.g., currency, stamps, or tokens).
-
E.
superunitOf
Indicates that one unit is hierarchically above and directly encompasses another unit within an organizational or structural system.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: May 1, 2026, 1:42 a.m.