Triple
T18307121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Silverman |
E438514
|
entity |
| Predicate | employedInFictionalUniverseBy |
P40735
|
FINISHED |
| Object | Hollywood film studio |
—
|
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: Hollywood film studio | Statement: [Joe Silverman, employedInFictionalUniverseBy, Hollywood film studio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedInFictionalUniverseBy Context triple: [Joe Silverman, employedInFictionalUniverseBy, Hollywood film studio]
-
A.
hasInUniverseRole
Indicates that an entity holds or performs a specific role or function within a particular fictional or defined universe.
-
B.
employerInUniverse
chosen
Indicates that one entity serves as the employer of another within a specified universe, context, or world.
-
C.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
D.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
E.
fictionalUniverseRole
Indicates the role or function an entity has within a particular fictional universe or narrative setting.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021519a481908a9b6561946f1c65 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.