Triple
T25641534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helix Innovations |
E642848
|
entity |
| Predicate | riskProfileClaim |
P158950
|
FINISHED |
| Object | smokeless alternative to cigarettes |
—
|
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: smokeless alternative to cigarettes | Statement: [Helix Innovations, riskProfileClaim, smokeless alternative to cigarettes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskProfileClaim Context triple: [Helix Innovations, riskProfileClaim, smokeless alternative to cigarettes]
-
A.
riskProfile
Indicates the level and characteristics of potential risk associated with an entity, action, or situation.
-
B.
riskReturnProfile
Indicates how the level of risk associated with an entity or investment corresponds to its expected or historical return.
-
C.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
D.
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.
-
E.
riskSensitivity
Indicates how strongly an entity’s decisions or behavior change in response to potential risk or uncertainty.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa660fa0819087e2711cee51d7a1 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 5:43 p.m.