Triple
T28643136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahr Kéita |
E724982
|
entity |
| Predicate | altNameLanguageContext |
P115647
|
FINISHED |
| Object | used in Francophone Central Africa maps |
—
|
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: used in Francophone Central Africa maps | Statement: [Bahr Kéita, altNameLanguageContext, used in Francophone Central Africa maps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: altNameLanguageContext Context triple: [Bahr Kéita, altNameLanguageContext, used in Francophone Central Africa maps]
-
A.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
B.
secondaryLanguageContext
chosen
Indicates that the associated information, interaction, or content occurs within or is tailored to a secondary (non-primary) language setting or usage context.
-
C.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
-
D.
labelNameLanguage
Indicates the language in which a given label or name is expressed.
-
E.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 4:46 a.m.