Triple
T26875993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proud |
E676748
|
entity |
| Predicate | hasActress |
P160083
|
FINISHED |
| Object | Keisha Nash Whitaker |
—
|
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: Keisha Nash Whitaker | Statement: [Proud, hasActress, Keisha Nash Whitaker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasActress Context triple: [Proud, hasActress, Keisha Nash Whitaker]
-
A.
hasAssociatedActress
chosen
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
B.
madeActressA
Indicates that one entity caused or was responsible for another entity becoming an actress.
-
C.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
D.
hasHumanCast
Indicates that a work or production features human performers as part of its cast.
-
E.
arePlayedBy
Indicates that one or more performers (such as actors or musicians) carry out, interpret, or execute the referenced roles, characters, or pieces.
- 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_69eee9bb44988190b6e11652d028bc59 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 5:36 a.m.