Triple
T23584262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onchocerciasis Elimination Program for the Americas |
E582293
|
entity |
| Predicate | targetsVector |
P152803
|
FINISHED |
| Object | Simulium blackflies |
—
|
NE NERFINISHED |
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: Simulium blackflies | Statement: [Onchocerciasis Elimination Program for the Americas, targetsVector, Simulium blackflies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsVector Context triple: [Onchocerciasis Elimination Program for the Americas, targetsVector, Simulium blackflies]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
C.
targetsSystems
Indicates that an entity is directed at, attacks, or is intended to affect specific systems.
-
D.
targetsField
Indicates that one entity is directed toward, focuses on, or is intended to affect a specific field or attribute of another entity.
-
E.
targetsVirus
Indicates that one entity is directed against, acts upon, or is specifically intended to affect a virus.
- 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_69e248f8d8248190acd5aee77f0d1709 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b02f68288190b348c7558a6a24e1 |
completed | April 29, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:40 p.m.