Triple
T18783865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diptera |
E459324
|
entity |
| Predicate | includesDiseaseVector |
P69337
|
FINISHED |
| Object | Anopheles mosquitoes |
—
|
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: Anopheles mosquitoes | Statement: [Diptera, includesDiseaseVector, Anopheles mosquitoes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesDiseaseVector Context triple: [Diptera, includesDiseaseVector, Anopheles mosquitoes]
-
A.
includesDisease
Indicates that one entity (such as a category, group, or collection) contains or encompasses a particular disease as part of its members or elements.
-
B.
diseaseVector
Indicates that one entity serves as a carrier or transmitter that spreads a disease-causing agent to another entity.
-
C.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
D.
targetsDiseaseVector
chosen
Indicates that an entity is directed at, designed to affect, or intended to control a particular disease-carrying vector organism.
-
E.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5977f34e48190a9932af330ea4f92 |
completed | April 20, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.