Triple
T19992666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APOE ε3 allele |
E494101
|
entity |
| Predicate | associatedWithTriglycerides |
P138248
|
FINISHED |
| Object | typical 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: typical levels | Statement: [APOE ε3 allele, associatedWithTriglycerides, typical levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTriglycerides Context triple: [APOE ε3 allele, associatedWithTriglycerides, typical levels]
-
A.
associatedWithDrug
Indicates that an entity has a relevant relationship or connection to a specific drug, such as use, exposure, or involvement in its context.
-
B.
associatedSin
Indicates a relationship where one entity is linked or connected to a particular sin or wrongful act.
-
C.
associatedWithUse
Indicates a relationship where one entity is connected to or involved in the use or utilization of another entity.
-
D.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
E.
commonlyIdentifiedWith
Indicates that two entities are widely regarded or treated as the same or equivalent, even if they are formally distinct.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe10ffc81908c94168b0a8ea9c9 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 11, 2026, 3:31 p.m.