Triple
T12544162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamanaka factors |
E299917
|
entity |
| Predicate | effectOnCell |
P94935
|
FINISHED |
| Object | convert differentiated cells to pluripotent state |
—
|
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: convert differentiated cells to pluripotent state | Statement: [Yamanaka factors, effectOnCell, convert differentiated cells to pluripotent state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnCell Context triple: [Yamanaka factors, effectOnCell, convert differentiated cells to pluripotent state]
-
A.
affectsCellType
chosen
Indicates that one entity produces an effect or change on a specific type of cell.
-
B.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
E.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.