Triple
T6307343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venturia inaequalis |
E141409
|
entity |
| Predicate | infectionRequires |
P69969
|
FINISHED |
| Object | leaf wetness |
—
|
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: leaf wetness | Statement: [Venturia inaequalis, infectionRequires, leaf wetness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: infectionRequires Context triple: [Venturia inaequalis, infectionRequires, leaf wetness]
-
A.
infectionType
Indicates the specific category or nature of an infection associated with an entity or event.
-
B.
riskFactorForInfection
Indicates that something increases the likelihood or susceptibility of an entity to develop a particular infection.
-
C.
requiresPremedication
Indicates that one entity must receive premedication (a preparatory medical treatment) before another specified procedure, treatment, or action can occur.
-
D.
infectsTissue
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another entity.
-
E.
requiresCare
Indicates that one entity depends on another to provide care, attention, or maintenance for its proper functioning or well-being.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647b69f08190bb085f9b700f6453 |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:28 p.m.