Triple
T38610702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Emperor Jones (1933 film) |
E934468
|
entity |
| Predicate | leadCharacterRoleLater |
P52440
|
FINISHED |
| Object | tyrannical ruler |
—
|
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: tyrannical ruler | Statement: [The Emperor Jones (1933 film), leadCharacterRoleLater, tyrannical ruler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterRoleLater Context triple: [The Emperor Jones (1933 film), leadCharacterRoleLater, tyrannical ruler]
-
A.
leadCharacterBasedOn
Indicates that a lead character is derived from, inspired by, or adapted from a particular source entity (such as a real person, another character, or existing work).
-
B.
leadCharacterCaste
Indicates that the lead character in a work belongs to a specified caste.
-
C.
leadCharacterField
Indicates that one entity serves as the primary or main character associated with another entity, such as a work or production.
-
D.
characterFutureRole
chosen
Indicates the role or position that a character is expected or intended to assume at a later point in time.
-
E.
leadRoleActor
Indicates that an actor performs a leading or principal role in a work or production.
- 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_69f76eccd6d081909ccce171011739a1 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.