Triple
T6004984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUS |
E133686
|
entity |
| Predicate | mutationEffect |
P39638
|
FINISHED |
| Object | cytoplasmic mislocalization |
—
|
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: cytoplasmic mislocalization | Statement: [FUS, mutationEffect, cytoplasmic mislocalization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mutationEffect Context triple: [FUS, mutationEffect, cytoplasmic mislocalization]
-
A.
modification
Indicates a change made to an existing entity, altering its properties, structure, or state from a prior version.
-
B.
tierEffect
Indicates how belonging to a particular tier influences or modifies the outcome, behavior, or properties associated with that tier.
-
C.
sideEffect
chosen
Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
-
D.
stateMutationMechanism
Indicates the process or method by which a system’s state is changed from one condition to another.
-
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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f10d18081908c351170b7f58d3d |
completed | March 22, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c049e3316c819087ea635fa7ee8472 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.