Triple
T29542165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebou |
E749530
|
entity |
| Predicate | culturalInfluenceOnCity |
P2008
|
FINISHED |
| Object | Dakar |
—
|
NE NERFINISHED |
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: Dakar | Statement: [Lebou, culturalInfluenceOnCity, Dakar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalInfluenceOnCity Context triple: [Lebou, culturalInfluenceOnCity, Dakar]
-
A.
cityOfInfluence
Indicates the city that significantly shapes, impacts, or exerts influence over a given entity.
-
B.
hasUrbanInfluence
Indicates that one entity exerts or reflects the characteristics, impact, or style of an urban area on another entity.
-
C.
hasCulturalImpact
chosen
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
D.
heritageInfluence
Indicates how one entity’s cultural, historical, or ancestral background affects or shapes another entity’s characteristics, behavior, or development.
-
E.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
- 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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 28, 2026, 5:03 p.m.