Triple
T321290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archaea |
E6420
|
entity |
| Predicate | metabolicDiversity |
P12476
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Archaea, metabolicDiversity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metabolicDiversity Context triple: [Archaea, metabolicDiversity, high]
-
A.
biota
Indicates the presence or composition of living organisms (flora, fauna, or other life forms) associated with a given entity or environment.
-
B.
biome
Indicates the type of ecological environment or habitat in which an entity naturally exists or is situated.
-
C.
biodiversityStatus
Indicates the current condition or level of biological diversity associated with an entity, often in terms of richness, health, or conservation concern.
-
D.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
E.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
- F. None of above. chosen
Provenance (4 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea81a1e88190b3496070eb3d85f5 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea7d03a88190aab72e61d8673488 |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.