Triple
T34091901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acomplia |
E874318
|
entity |
| Predicate | effectOnTriglycerides |
P138248
|
FINISHED |
| Object | reduces triglyceride levels |
—
|
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: reduces triglyceride levels | Statement: [Acomplia, effectOnTriglycerides, reduces triglyceride levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnTriglycerides Context triple: [Acomplia, effectOnTriglycerides, reduces triglyceride levels]
-
A.
associatedWithTriglycerides
chosen
Indicates a relationship in which something has a connection or relevance to triglycerides, such as influencing, being influenced by, or otherwise linked to them.
-
B.
associatedWithLipidMetabolism
Indicates a relationship where a process, molecule, or entity is involved in, influences, or is functionally connected to lipid metabolism.
-
C.
glycerolEffect
Indicates the effect or influence that glycerol has on another entity, condition, or process.
-
D.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
E.
isLipid
Indicates that the subject entity is classified as a lipid or belongs to the category of lipid molecules.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 1, 2026, 1:52 a.m.