Triple
T26409455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hogbonu |
E663918
|
entity |
| Predicate | traditionalNameInLanguage |
P21030
|
FINISHED |
| Object | Yoruba |
—
|
NE NERFINISHED |
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: Yoruba | Statement: [Hogbonu, traditionalNameInLanguage, Yoruba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalNameInLanguage Context triple: [Hogbonu, traditionalNameInLanguage, Yoruba]
-
A.
traditionalLanguageName
chosen
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
B.
languageTraditionally
Indicates that something is customarily or historically expressed, written, or communicated in a particular language.
-
C.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
D.
originalNameLanguage
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
E.
languageFamilyTraditional
Indicates that one entity belongs to, or is classified under, the traditional language family of the other 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 26, 2026, 11:37 p.m.