Triple
T31993848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persian tobacco concession |
E816939
|
entity |
| Predicate | compensationPaidToCompany |
P88497
|
FINISHED |
| Object | 500000 pounds sterling |
—
|
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: 500000 pounds sterling | Statement: [Persian tobacco concession, compensationPaidToCompany, 500000 pounds sterling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compensationPaidToCompany Context triple: [Persian tobacco concession, compensationPaidToCompany, 500000 pounds sterling]
-
A.
providedCompensationAmount
chosen
Indicates the specific amount of compensation that was given or agreed to be given in relation to an action, event, or obligation.
-
B.
compensationModel
Indicates the type or structure of payment or rewards provided in exchange for work, services, or performance.
-
C.
compensationCategory
Indicates the type or classification of compensation associated with an entity, such as how or in what form payment or remuneration is provided.
-
D.
compensationRate
Indicates the rate or amount of payment provided in exchange for a specified unit of work, time, or service.
-
E.
compensationIncludes
Indicates that a specified form of payment or benefit is part of the overall compensation provided in a given context.
- 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_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: May 1, 2026, 12:13 a.m.