Triple
T14003103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monumental Pictures |
E336878
|
entity |
| Predicate | fictionalBusinessType |
P81118
|
FINISHED |
| Object | Hollywood 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 studio | Statement: [Monumental Pictures, fictionalBusinessType, Hollywood studio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalBusinessType Context triple: [Monumental Pictures, fictionalBusinessType, Hollywood studio]
-
A.
fictionalEntityType
chosen
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
B.
fictionalOrganizationFeatured
Indicates that a fictional organization is prominently presented or plays a significant role within a given work or context.
-
C.
fictionalOrganizationName
Indicates that the relationship specifies the name assigned to a fictional organization.
-
D.
fictionalIndustry
Indicates that an entity operates within an industry or sector that exists only in fiction rather than in the real world.
-
E.
fictionalService
Indicates that one entity provides or is associated with an imagined or non-real service in relation to another entity.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed06a50819093ddc64f55050689 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.