Triple
T3781690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boma – Flavors of Africa |
E85431
|
entity |
| Predicate | buffetFocus |
P9631
|
FINISHED |
| Object | dishes from across the African continent |
—
|
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: dishes from across the African continent | Statement: [Boma – Flavors of Africa, buffetFocus, dishes from across the African continent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buffetFocus Context triple: [Boma – Flavors of Africa, buffetFocus, dishes from across the African continent]
-
A.
offersBuffet
Indicates that one entity provides a buffet-style service or meal option to another entity.
-
B.
feastType
Indicates the specific kind or category of feast associated with an event or occasion.
-
C.
diningStyle
chosen
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
feast
Indicates that an entity participates in or hosts a large, elaborate meal or celebration involving abundant food and communal dining.
-
E.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:13 p.m.