Triple
T1604730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ga people |
E34474
|
entity |
| Predicate | urbanInfluence |
P21809
|
FINISHED |
| Object | Accra popular culture |
—
|
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: Accra popular culture | Statement: [Ga people, urbanInfluence, Accra popular culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanInfluence Context triple: [Ga people, urbanInfluence, Accra popular culture]
-
A.
cityOfInfluence
chosen
Indicates the city that significantly shapes, impacts, or exerts influence over a given entity.
-
B.
urbanDevelopment
Indicates the process or activities through which urban areas are planned, expanded, or transformed, including changes to infrastructure, land use, and the built environment.
-
C.
urbanDesign
Indicates the relationship in which an entity is responsible for planning, organizing, or shaping the physical layout and functional structure of urban spaces.
-
D.
withinUrbanArea
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
- 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fa6926081908bc78d15c0be3185 |
completed | March 5, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69a907c35f848190a2428c52e81d013e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.