Triple
T23612514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derek Wills |
E583084
|
entity |
| Predicate | creativeRoleInFiction |
P19360
|
FINISHED |
| Object | director of Bombshell |
—
|
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: director of Bombshell | Statement: [Derek Wills, creativeRoleInFiction, director of Bombshell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creativeRoleInFiction Context triple: [Derek Wills, creativeRoleInFiction, director of Bombshell]
-
A.
creativeRole
chosen
Indicates that an entity holds a specific creative function or responsibility in relation to another entity, such as a work or project.
-
B.
fictionalOccupation
Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
-
C.
fictionalPersonaOf
Indicates that one entity is a fictional or narrative persona, alter ego, or character representation of another (typically real or primary) entity.
-
D.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
E.
fictionalCharacterAssisted
Indicates that one fictional character provided help, support, or assistance to another fictional character.
- 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_69e248fbcd9081908ba08913f9d30826 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0f582148190a525119aa51b9b84 |
completed | April 29, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:45 p.m.