Triple
T11648395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Equatorial Guinea |
E276836
|
entity |
| Predicate | treeCommonName |
P570
|
FINISHED |
| Object | silk-cotton tree |
—
|
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: silk-cotton tree | Statement: [coat of arms of Equatorial Guinea, treeCommonName, silk-cotton tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treeCommonName Context triple: [coat of arms of Equatorial Guinea, treeCommonName, silk-cotton tree]
-
A.
dominantTreeCommonName
Indicates the common (non-scientific) name of the tree species that is dominant in a given area or ecological context.
-
B.
commonTreeType
Indicates that two or more entities share the same type or classification of tree.
-
C.
otherCommonName
Indicates that an entity is known by an additional, alternative common name besides its primary one.
-
D.
hasSurroundingTreeCommonName
Indicates that an entity is associated with a surrounding tree identified by its common (vernacular) name.
-
E.
commonName
chosen
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cd9bb0819093d107204bed2fe0 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.