Triple
T10263396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camel Turkish Gold |
E240654
|
entity |
| Predicate | associatedRiskFactor |
P62537
|
FINISHED |
| Object | addiction |
—
|
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: addiction | Statement: [Camel Turkish Gold, associatedRiskFactor, addiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedRiskFactor Context triple: [Camel Turkish Gold, associatedRiskFactor, addiction]
-
A.
riskFactorTypeStudied
Indicates that a particular type of risk factor is the subject of study or analysis in a given context.
-
B.
riskFactorForInfection
Indicates that something increases the likelihood or susceptibility of an entity to develop a particular infection.
-
C.
epidemiologicalRisk
Indicates a relationship where one entity poses or is associated with a potential risk of disease occurrence, transmission, or impact to another entity or population from an epidemiological perspective.
-
D.
riskElement
chosen
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
E.
riskFeature
Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:33 a.m.