Triple
T6005996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candida albicans |
E133710
|
entity |
| Predicate | becomesPathogenicUnder |
P68700
|
FINISHED |
| Object | immunosuppression |
—
|
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: immunosuppression | Statement: [Candida albicans, becomesPathogenicUnder, immunosuppression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becomesPathogenicUnder Context triple: [Candida albicans, becomesPathogenicUnder, immunosuppression]
-
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.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
-
D.
carriesPathogen
Indicates that one entity harbors and can transmit a disease-causing pathogen to another entity or environment.
-
E.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
- 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_69c04f128354819088971ee398cbda77 |
completed | March 22, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
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.