Triple
T37450227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchnera |
E930652
|
entity |
| Predicate | impactOnHostFitness |
P121603
|
FINISHED |
| Object | essential for normal aphid growth and reproduction |
—
|
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: essential for normal aphid growth and reproduction | Statement: [Buchnera, impactOnHostFitness, essential for normal aphid growth and reproduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnHostFitness Context triple: [Buchnera, impactOnHostFitness, essential for normal aphid growth and reproduction]
-
A.
hostImpact
Indicates that one entity causes an effect, influence, or change on another entity that acts as its host.
-
B.
impactOnReproduction
chosen
Indicates a relationship where one entity affects, alters, or influences the reproductive capacity, success, or processes of another entity.
-
C.
impactOnPerformance
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
-
D.
larvalEffectOnHost
Indicates the impact or influence that larvae have on their host organism.
-
E.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
- 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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:17 p.m.