Triple
T12653876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobo |
E302231
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Bobo-Madaré |
E856367
|
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: Bobo-Madaré | Statement: [Bobo, hasAlternativeName, Bobo-Madaré]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobo-Madaré Context triple: [Bobo, hasAlternativeName, Bobo-Madaré]
-
A.
Mr. Bobo
Mr. Bobo is an eccentric, retired circus performer who lives upstairs from Coraline and obsessively trains a troupe of jumping mice in Neil Gaiman’s novella "Coraline."
-
B.
Bobo
Bobo is a major Mande language spoken primarily in parts of West Africa, notably in Burkina Faso and Mali.
-
C.
Bobo
chosen
The Bobo are an ethnic group of West Africa, primarily living in western Burkina Faso and known for their farming traditions and rich mask-based ceremonial culture.
-
D.
Bobo-Dioulassien
Bobo-Dioulassien refers to an inhabitant or native of Bobo-Dioulasso, a major city in southwestern Burkina Faso.
-
E.
Banzi
Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96160730c81909e1aa3efb51bf159 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688104d48190939933b93b7e60cc |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:18 p.m.