Triple
T22691763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lark |
E561067
|
entity |
| Predicate | hasAddictiveComponent |
P41092
|
FINISHED |
| Object | nicotine |
—
|
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: nicotine | Statement: [Lark, hasAddictiveComponent, nicotine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAddictiveComponent Context triple: [Lark, hasAddictiveComponent, nicotine]
-
A.
hasAddictiveSubstance
chosen
Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
-
B.
hasAddictionPotential
Indicates that one entity (typically a substance or activity) has the capacity to cause another entity (typically a person) to develop dependence or addictive behavior toward it.
-
C.
hasFictionalSubstance
Indicates that one entity includes, contains, or involves a fictional or imaginary substance as part of its composition, setting, or narrative.
-
D.
canBeDopedWith
Indicates that one entity is capable of being modified or enhanced by introducing the other entity as a dopant.
-
E.
hasLowAddictionPotential
Indicates that the associated substance, activity, or behavior is unlikely to lead to dependence or compulsive use.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789adcc48190b4a717166d5dba19 |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.