Triple
T34658696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banisteriopsis caapi |
E890048
|
entity |
| Predicate | effectOnDMT |
P193271
|
FINISHED |
| Object | enables oral activity of DMT in ayahuasca |
—
|
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: enables oral activity of DMT in ayahuasca | Statement: [Banisteriopsis caapi, effectOnDMT, enables oral activity of DMT in ayahuasca]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnDMT Context triple: [Banisteriopsis caapi, effectOnDMT, enables oral activity of DMT in ayahuasca]
-
A.
psychoactiveProfile
Indicates the characteristic pattern of psychoactive effects or mental state changes produced by a substance, treatment, or exposure.
-
B.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
E.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
- 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
| PDg | Predicate description generation | batch_69fd3d45ccb8819082f15e60bd33afc9 |
completed | May 8, 2026, 1:32 a.m. |
Created at: May 1, 2026, 2:04 a.m.