Triple
T16150615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solenopsis invicta virus 1 |
E391899
|
entity |
| Predicate | effectOnHost |
P58916
|
FINISHED |
| Object | reduces worker longevity |
—
|
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: reduces worker longevity | Statement: [Solenopsis invicta virus 1, effectOnHost, reduces worker longevity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnHost Context triple: [Solenopsis invicta virus 1, effectOnHost, reduces worker longevity]
-
A.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
B.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
C.
effectOnOthers
chosen
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
D.
effectOnMachines
Indicates the influence or impact that one entity, condition, or action has on machines and their behavior or performance.
-
E.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9724808190a8332987583a345a |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.