Triple
T7273994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dioula |
E162977
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Jula |
E302226
|
NE 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: Jula | Statement: [Dioula, hasAlternativeName, Jula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jula Context triple: [Dioula, hasAlternativeName, Jula]
-
A.
Jula
chosen
Jula is a major Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
-
B.
Jule
Jule is a given name most notably associated with Jule Gregory Charney, a pioneering American meteorologist and one of the founders of modern numerical weather prediction.
-
C.
Juliaetta
Juliaetta is a small rural city in north-central Idaho, known for its agricultural surroundings and location in the Clearwater River region.
-
D.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
E.
Júlia
Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0de9f48190807dd148758bad62 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db2936dc8190aed38888bb5e47b8 |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:58 p.m.