Triple
T6005942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neurospora crassa |
E133709
|
entity |
| Predicate | temperatureOptimum |
P40203
|
FINISHED |
| Object | around 25 to 30 degrees Celsius |
—
|
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: around 25 to 30 degrees Celsius | Statement: [Neurospora crassa, temperatureOptimum, around 25 to 30 degrees Celsius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temperatureOptimum Context triple: [Neurospora crassa, temperatureOptimum, around 25 to 30 degrees Celsius]
-
A.
operatingTemperature
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
B.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
C.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
D.
growthTemperatureRange
chosen
Indicates the range of temperatures within which an organism or entity can grow or function effectively.
-
E.
hasTemperatureRegime
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f128354819088971ee398cbda77 |
completed | March 22, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.