Triple
T13574525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | African bush elephant |
E324246
|
entity |
| Predicate | hasIUCNRedListCategory |
P1339
|
FINISHED |
| Object | Endangered |
—
|
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: Endangered | Statement: [African bush elephant, hasIUCNRedListCategory, Endangered]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIUCNRedListCategory Context triple: [African bush elephant, hasIUCNRedListCategory, Endangered]
-
A.
conservationStatus
chosen
Indicates the level of risk or protection category assigned to an entity, typically reflecting how threatened it is with extinction or decline.
-
B.
IUCNStatusSystem
Indicates the conservation status classification framework used to assign an IUCN threat category to a species or taxon.
-
C.
wildlifeProtectionStatus
Indicates the level or type of legal or conservation protection currently applied to wildlife.
-
D.
protectedAreaIUCNCategory
Indicates the specific IUCN management category assigned to a protected area, describing the type and level of its conservation protection.
-
E.
hasConservationConcernIn
Indicates that an entity is subject to a specified conservation concern status within a particular geographic area or jurisdiction.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.