Triple
T2151179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winston |
E47182
|
entity |
| Predicate | nicotineLevel |
P36262
|
FINISHED |
| Object | various depending on variant |
—
|
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: various depending on variant | Statement: [Winston, nicotineLevel, various depending on variant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicotineLevel Context triple: [Winston, nicotineLevel, various depending on variant]
-
A.
smokeUse
Indicates that an entity uses or consumes tobacco or other substances by smoking.
-
B.
isNonSmoking
Indicates that the subject is designated or required to be free from smoking or tobacco use.
-
C.
smokedOver
Indicates that one entity smoked (used tobacco or similar substances) for a duration exceeding a specified time or threshold.
-
D.
tanninLevel
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
E.
alcoholLevel
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe4747a0819080e2234f3ea8995f |
completed | March 7, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe4252688190944491a450383450 |
completed | March 7, 2026, 5:57 a.m. |
Created at: March 4, 2026, 7:44 p.m.