Triple
T15141743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Botswana |
E361699
|
entity |
| Predicate | ivoryTuskSymbolizes |
P34702
|
FINISHED |
| Object | wildlife conservation |
—
|
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: wildlife conservation | Statement: [Coat of arms of Botswana, ivoryTuskSymbolizes, wildlife conservation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ivoryTuskSymbolizes Context triple: [Coat of arms of Botswana, ivoryTuskSymbolizes, wildlife conservation]
-
A.
hasTuskMaterial
Indicates that an entity’s tusks are made of, or composed from, a specified material.
-
B.
hasTusk
Indicates that an entity possesses one or more tusks as a physical feature.
-
C.
animalSymbol
Indicates that one entity serves as a symbolic representation or emblem of the other in the form of an animal.
-
D.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
E.
emblemSymbolism
chosen
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c5c4248190b57234e3ccf2831b |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.