Triple
T20783561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricky Verona |
E511568
|
entity |
| Predicate | usesPoisonType |
P8036
|
FINISHED |
| Object | synthetic Beijing cocktail |
—
|
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: synthetic Beijing cocktail | Statement: [Ricky Verona, usesPoisonType, synthetic Beijing cocktail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPoisonType Context triple: [Ricky Verona, usesPoisonType, synthetic Beijing cocktail]
-
A.
poisonUsed
Indicates that one entity employed poison as a means to harm, kill, or incapacitate another entity.
-
B.
toxinType
chosen
Indicates the specific kind or category of toxin associated with an entity.
-
C.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
D.
toxinEffect
Indicates the harmful impact or physiological response caused by a toxin on a target entity.
-
E.
venomous
Indicates that an organism possesses venom and can inject or deliver it to another organism, typically as a means of defense or predation.
- 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28a4584819084d2d02febe47001 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:38 p.m.