Triple
T1209986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinar del Río Province |
E25975
|
entity |
| Predicate | VueltabajoKnownFor |
P24677
|
FINISHED |
| Object | high-quality tobacco |
—
|
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: high-quality tobacco | Statement: [Pinar del Río Province, VueltabajoKnownFor, high-quality tobacco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VueltabajoKnownFor Context triple: [Pinar del Río Province, VueltabajoKnownFor, high-quality tobacco]
-
A.
alsoKnownFor
Indicates that an entity is additionally recognized or noted for another work, role, achievement, or characteristic beyond its primary association.
-
B.
underlyingKnownFor
Indicates that one entity is fundamentally or primarily recognized as the basis or main reason for another entity’s notability or fame.
-
C.
developerOfWorkAppearingIn
Indicates that one entity is the creator or developer of a work in which another entity appears or is featured.
-
D.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
E.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
- F. None of above. chosen
Provenance (4 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde4670481908c16a3a8c1a54aad |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6078088190ba0221ae3368416c |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbf83584819088c69366f58586cc |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:46 p.m.