Triple
T29020082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opisthosporidia |
E737425
|
entity |
| Predicate | hasPathogenicity |
P41034
|
FINISHED |
| Object | can be pathogenic to protists |
—
|
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: can be pathogenic to protists | Statement: [Opisthosporidia, hasPathogenicity, can be pathogenic to protists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPathogenicity Context triple: [Opisthosporidia, hasPathogenicity, can be pathogenic to protists]
-
A.
pathogenicity
chosen
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.
pathogenicMember
Indicates that an entity is a member of a group or set that is characterized as pathogenic (capable of causing disease).
-
D.
becomesPathogenicUnder
Indicates that an entity transitions into a disease-causing or harmful state when exposed to a specified condition or factor.
-
E.
pathogenicMechanism
Indicates the specific biological process or mechanism through which an agent causes disease or pathological effects in a host.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 28, 2026, 9:48 a.m.