Triple
T16676460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radio Ethiopia |
E405225
|
entity |
| Predicate | featuresStyleElement |
P124216
|
FINISHED |
| Object | spoken word poetry |
—
|
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: spoken word poetry | Statement: [Radio Ethiopia, featuresStyleElement, spoken word poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresStyleElement Context triple: [Radio Ethiopia, featuresStyleElement, spoken word poetry]
-
A.
featuresStyle
Indicates that one entity exhibits, incorporates, or is characterized by a particular style associated with another entity.
-
B.
stylingFeature
Indicates a visual or design-related characteristic applied to an entity, such as formatting, layout, or aesthetic treatment.
-
C.
notableStyleFeature
Indicates that an entity possesses a distinctive stylistic characteristic or design element that is especially noteworthy or defining.
-
D.
styleLanguage
Indicates a relationship where one entity specifies the language or linguistic style in which another entity is expressed, formatted, or presented.
-
E.
structuralStyle
Indicates the architectural or design style that characterizes the structure or form of an entity.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6b69cc8190b19632e1b4293569 |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.