Triple
T21510517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuelta Abajo tobacco-growing region |
E530704
|
entity |
| Predicate | tobaccoUse |
P101044
|
FINISHED |
| Object | wrappers for many top-tier Cuban cigar brands |
—
|
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: wrappers for many top-tier Cuban cigar brands | Statement: [Vuelta Abajo tobacco-growing region, tobaccoUse, wrappers for many top-tier Cuban cigar brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tobaccoUse Context triple: [Vuelta Abajo tobacco-growing region, tobaccoUse, wrappers for many top-tier Cuban cigar brands]
-
A.
smokeUse
Indicates that an entity uses or consumes tobacco or other substances by smoking.
-
B.
usesTobaccoType
Indicates that an entity consumes or makes use of a specified type or form of tobacco.
-
C.
containsTobacco
chosen
Indicates that one entity includes tobacco as a component, ingredient, or constituent part of itself.
-
D.
tobaccoRepresents
Indicates that one entity symbolically stands for, signifies, or is used as a representation of tobacco in some context.
-
E.
containsNicotine
Indicates that the subject has nicotine as one of its components or ingredients.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.