Triple
T5168962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asiento granted to Britain |
E116626
|
entity |
| Predicate | effectOnBritain |
P27108
|
FINISHED |
| Object | increase in profits from slave trading |
—
|
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: increase in profits from slave trading | Statement: [Asiento granted to Britain, effectOnBritain, increase in profits from slave trading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnBritain Context triple: [Asiento granted to Britain, effectOnBritain, increase in profits from slave trading]
-
A.
resultForGreatBritain
chosen
Indicates the outcome or performance achieved specifically by Great Britain in a given event, context, or measurement.
-
B.
regionAllocatedToBritain
Indicates that a specific geographic region has been designated or assigned to Britain’s control or authority.
-
C.
effectOnSpain
Indicates a relationship where one entity produces an influence, change, or consequence specifically affecting Spain.
-
D.
effectOnDutchRepublic
Indicates the impact or consequences that something has on the Dutch Republic.
-
E.
strength_British_side
Indicates the level or measure of military or strategic power possessed by the British side 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd794dd9988190922e138f2a9a3c62 |
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.