Triple
T3781682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boma – Flavors of Africa |
E85431
|
entity |
| Predicate | offersVeganOptions |
P34157
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Boma – Flavors of Africa, offersVeganOptions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersVeganOptions Context triple: [Boma – Flavors of Africa, offersVeganOptions, true]
-
A.
offersCuisine
Indicates that one entity provides or serves a particular type or style of cuisine to others.
-
B.
dietaryOptions
chosen
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
C.
offersBuffet
Indicates that one entity provides a buffet-style service or meal option to another entity.
-
D.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
E.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
- 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.