Triple
T31993834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persian tobacco concession |
E816939
|
entity |
| Predicate | royaltyRate |
P79387
|
FINISHED |
| Object | 25 percent of net profits |
—
|
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: 25 percent of net profits | Statement: [Persian tobacco concession, royaltyRate, 25 percent of net profits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: royaltyRate Context triple: [Persian tobacco concession, royaltyRate, 25 percent of net profits]
-
A.
royaltyRateOnProduction
chosen
Indicates the percentage or amount of royalty that must be paid based on the level or value of production.
-
B.
associatedWithRoyalty
Indicates a relationship in which an entity has a notable connection to royalty, such as through lineage, service, patronage, or symbolic affiliation.
-
C.
commissionType
Indicates the specific kind or category of commission arrangement that applies to a given transaction or relationship.
-
D.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
E.
originalRate
Indicates the initial or base rate associated with something before any changes, adjustments, or discounts are applied.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b3bdbcb08190b9fe7baf11e612a5 |
completed | May 3, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:13 a.m.