Triple
T10423882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arctic fox |
E245732
|
entity |
| Predicate | thermalAdaptation |
P9108
|
FINISHED |
| Object | can withstand very low temperatures |
—
|
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: can withstand very low temperatures | Statement: [Arctic fox, thermalAdaptation, can withstand very low temperatures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thermalAdaptation Context triple: [Arctic fox, thermalAdaptation, can withstand very low temperatures]
-
A.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
B.
adaptationIn
Indicates that something appears, is represented, or takes place within a particular adaptation of an original work.
-
C.
bodyTemperatureRegulation
chosen
Indicates how an entity controls or maintains its internal body temperature in response to environmental conditions.
-
D.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
E.
hasHumanAdaptation
Indicates that something has been modified, designed, or adjusted specifically to suit human use, abilities, or needs.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2de4d48190aee65b3f6ec3cc48 |
completed | April 7, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:12 p.m.