Triple
T16581617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Region Government of Nigeria |
E402844
|
entity |
| Predicate | usedCommonLanguage |
P72909
|
FINISHED |
| Object | Yoruba |
—
|
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: Yoruba | Statement: [Western Region Government of Nigeria, usedCommonLanguage, Yoruba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedCommonLanguage Context triple: [Western Region Government of Nigeria, usedCommonLanguage, Yoruba]
-
A.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
C.
typicalLanguageUse
chosen
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
D.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
E.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35998371c8190936dcdaab5ca7e21 |
completed | April 18, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.