Triple
T14426931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yersinia |
E357719
|
entity |
| Predicate | canGrowAt |
P8732
|
FINISHED |
| Object | low temperatures near refrigeration |
—
|
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: low temperatures near refrigeration | Statement: [Yersinia, canGrowAt, low temperatures near refrigeration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canGrowAt Context triple: [Yersinia, canGrowAt, low temperatures near refrigeration]
-
A.
isGrowingAs
Indicates that one entity is developing, evolving, or increasing in some capacity in the manner or role specified by another entity.
-
B.
growsIn
chosen
Indicates that one entity develops, thrives, or increases in size or number within a specified environment, medium, or location.
-
C.
hasGrowthHabit
Indicates the characteristic way in which an organism typically grows or develops in form or structure.
-
D.
hasSecondaryGrowth
Indicates that an organism or structure undergoes secondary growth, meaning it increases in thickness or girth after its initial (primary) growth phase.
-
E.
hasGrowthRate
Indicates the rate at which something increases in size, quantity, or value over a given period of time.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de911398f08190be85bc0a8bef6b1b |
completed | April 14, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.