Triple
T35122863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar n Spice |
E1014210
|
entity |
| Predicate | hasDistinctRole |
P199354
|
FINISHED |
| Object | specialized area inside Mama Africa |
—
|
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: specialized area inside Mama Africa | Statement: [Sugar n Spice, hasDistinctRole, specialized area inside Mama Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctRole Context triple: [Sugar n Spice, hasDistinctRole, specialized area inside Mama Africa]
-
A.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
B.
hasRoleDistribution
Indicates how roles, responsibilities, or functions are allocated or distributed among entities within a given context.
-
C.
hasRoleCharacteristic
Indicates that an entity possesses a specific characteristic, quality, or attribute associated with a particular role.
-
D.
hasAuxiliaryRole
Indicates that an entity serves in a supporting or secondary capacity to another entity or primary role.
-
E.
hasEquivalentRole
Indicates that two entities hold roles that are functionally the same or interchangeable in a given context.
- F. None of above. chosen
Provenance (4 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69ff2fb9e46c8190b36b3e0bc84f114c |
completed | May 9, 2026, 12:59 p.m. |
Created at: May 3, 2026, 4:01 p.m.