Triple
T5168223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iranian toman |
E116610
|
entity |
| Predicate | subunitRelation |
P507
|
FINISHED |
| Object | 1 toman = 10 rials (informal usage) |
—
|
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: 1 toman = 10 rials (informal usage) | Statement: [Iranian toman, subunitRelation, 1 toman = 10 rials (informal usage)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subunitRelation Context triple: [Iranian toman, subunitRelation, 1 toman = 10 rials (informal usage)]
-
A.
subunitOf
Indicates that one entity functions as a component or smaller part within the structure or organization of another, larger entity.
-
B.
subunitType
Indicates that one entity is a specific kind or classification of subunit within the structure or composition of another entity.
-
C.
subunitRatio
chosen
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
-
D.
formerSubunit
Indicates that one entity was previously a subunit or subordinate part of another entity, but no longer holds that status.
-
E.
submultipleRelation
Indicates that one quantity is an exact submultiple of another, meaning it divides the other quantity into an integer number of equal parts.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd794b87508190be3b82726ef4b37c |
completed | March 20, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69bd77b36c008190b91011a9fa52b3d2 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:45 p.m.