Triple
T34949909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee Colored Children |
E1007960
|
entity |
| Predicate | directorEthnicBackground |
P193953
|
FINISHED |
| Object | Nigerian |
—
|
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: Nigerian | Statement: [Coffee Colored Children, directorEthnicBackground, Nigerian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: directorEthnicBackground Context triple: [Coffee Colored Children, directorEthnicBackground, Nigerian]
-
A.
directorEthnicity
chosen
Indicates the ethnic background or heritage associated with a director.
-
B.
leadActorEthnicity
Indicates the ethnic background or identity of the primary (lead) actor in a work.
-
C.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
D.
directorOccupation
Indicates that the specified occupation is the professional role or job held by the director.
-
E.
directorDescribedAs
Indicates that a director is characterized or portrayed using a particular description, label, or set of attributes.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 3, 2026, 4 p.m.