Triple
T28572310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Senegal |
E723145
|
entity |
| Predicate | baobabSymbolizes |
P145830
|
FINISHED |
| Object | endurance |
—
|
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: endurance | Statement: [Coat of arms of Senegal, baobabSymbolizes, endurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baobabSymbolizes Context triple: [Coat of arms of Senegal, baobabSymbolizes, endurance]
-
A.
treeSymbolism
Indicates the use of a tree as a symbolic representation of an idea, quality, or relationship between entities.
-
B.
plantSymbolism
chosen
Indicates that a plant is associated with a particular symbolic meaning, concept, or value.
-
C.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
D.
sacredTree
Indicates that an entity is regarded as a sacred or holy tree within a religious, spiritual, or cultural context.
-
E.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
- 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_69f01d7e97708190ae9e77ee66a68abd |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65093d9488190bc1e5c562b58f1e5 |
completed | May 2, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 4:10 a.m.