Triple
T6004825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C9orf72 |
E133683
|
entity |
| Predicate | pathogenicMechanism |
P68675
|
FINISHED |
| Object | haploinsufficiency |
—
|
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: haploinsufficiency | Statement: [C9orf72, pathogenicMechanism, haploinsufficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathogenicMechanism Context triple: [C9orf72, pathogenicMechanism, haploinsufficiency]
-
A.
pathogenicity
Indicates that one entity has the capacity to cause disease or harmful pathological effects in another entity.
-
B.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
C.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
D.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
-
E.
carriesPathogen
Indicates that one entity harbors and can transmit a disease-causing pathogen to another entity or environment.
- 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_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. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:06 p.m.