Triple
T78065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Browne & Williamson |
E1561
|
entity |
| Predicate | typeOfBusiness |
P3066
|
FINISHED |
| Object | manufacturer |
—
|
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: manufacturer | Statement: [Browne & Williamson, typeOfBusiness, manufacturer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBusiness Context triple: [Browne & Williamson, typeOfBusiness, manufacturer]
-
A.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
typeOfWork
Indicates the kind or category of work associated with or performed by an entity.
-
C.
legalPersonality
Indicates that an entity possesses recognized legal status, enabling it to hold rights, bear obligations, and act as a subject under the law.
-
D.
economicClassification
chosen
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
E.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.