Triple
T36627942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taraji P. Henson |
E904226
|
entity |
| Predicate | portraysCaregiverFigureIn |
P198531
|
FINISHED |
| Object | The Curious Case of Benjamin Button |
—
|
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: The Curious Case of Benjamin Button | Statement: [Taraji P. Henson, portraysCaregiverFigureIn, The Curious Case of Benjamin Button]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysCaregiverFigureIn Context triple: [Taraji P. Henson, portraysCaregiverFigureIn, The Curious Case of Benjamin Button]
-
A.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
B.
caregiverOf
Indicates a relationship where one entity provides ongoing care, support, or supervision for another entity’s well-being.
-
C.
depictsPersonRole
Indicates that an image or representation shows a person in a specific role, function, or capacity.
-
D.
portraysCharacterIn
chosen
Indicates that one entity depicts or represents a particular character within a work, such as a film, show, or other narrative medium.
-
E.
portraysCharacterWithDisability
Indicates that an entity depicts or represents a character who has a disability.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff79e7206c8190a809b5f2a6261378 |
completed | May 9, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69ff798356b881908645074fb3a96517 |
completed | May 9, 2026, 6:14 p.m. |
Created at: May 3, 2026, 4:11 p.m.