Triple
T23835463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valsaceae |
E590839
|
entity |
| Predicate | pathogenicPhase |
P144159
|
FINISHED |
| Object | canker formation on stems and branches |
—
|
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: canker formation on stems and branches | Statement: [Valsaceae, pathogenicPhase, canker formation on stems and branches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathogenicPhase Context triple: [Valsaceae, pathogenicPhase, canker formation on stems and branches]
-
A.
infectionPhase
chosen
Indicates the specific stage or period within the course of an infection that an entity is currently experiencing.
-
B.
pathogenicity
Indicates that one entity has the capacity to cause disease or harmful pathological effects in another entity.
-
C.
becomesPathogenicUnder
Indicates that an entity transitions into a disease-causing or harmful state when exposed to a specified condition or factor.
-
D.
pathogenicMechanism
Indicates the specific biological process or mechanism through which an agent causes disease or pathological effects in a host.
-
E.
pathogenicMember
Indicates that an entity is a member of a group or set that is characterized as pathogenic (capable of causing disease).
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f9eaa081909531f1322e0ec9ca |
completed | April 29, 2026, 8:57 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8:07 p.m.