Triple
T10224187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Bailey |
E242658
|
entity |
| Predicate | hasEmployerRole |
P13957
|
FINISHED |
| Object | oversees development and production of live-action features |
—
|
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: oversees development and production of live-action features | Statement: [Sean Bailey, hasEmployerRole, oversees development and production of live-action features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployerRole Context triple: [Sean Bailey, hasEmployerRole, oversees development and production of live-action features]
-
A.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
B.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
C.
hasAuthorEmployer
Indicates that the specified organization or entity is the employer of the author in question.
-
D.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
E.
hasMarketRole
Indicates that an entity holds or performs a specific functional role within a market or marketplace context.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa84a9ac819093d551005a1c8f3d |
completed | April 6, 2026, 12:43 p.m. |
| PD | Predicate disambiguation | batch_69d3955f61f88190b8d37ff645cd44d3 |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:11 a.m.