Triple
T37746794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paenibacillus |
E940864
|
entity |
| Predicate | biocontrolMechanism |
P43307
|
FINISHED |
| Object | antifungal compound production |
—
|
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: antifungal compound production | Statement: [Paenibacillus, biocontrolMechanism, antifungal compound production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: biocontrolMechanism Context triple: [Paenibacillus, biocontrolMechanism, antifungal compound production]
-
A.
preyControl
Indicates that one entity regulates, suppresses, or manages the population or behavior of another entity that serves as its prey.
-
B.
isEntomopathogenic
Indicates that an organism causes disease or death specifically in insects.
-
C.
speciesControlled
Indicates that one entity exerts control, management, or regulatory influence over a particular species.
-
D.
controlInnovation
Indicates that one entity directs, regulates, or significantly influences the innovation activities or outcomes of another entity.
-
E.
controlMethods
chosen
Indicates the methods or techniques used by one entity to direct, regulate, or influence the behavior, operation, or state of another entity.
- 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_69f76ee0e32c8190b40a3b4cf590337c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.