Triple
T15947664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph I. Breen |
E386725
|
entity |
| Predicate | genreRegulated |
P16785
|
FINISHED |
| Object | feature films |
—
|
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: feature films | Statement: [Joseph I. Breen, genreRegulated, feature films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreRegulated Context triple: [Joseph I. Breen, genreRegulated, feature films]
-
A.
genreRestriction
chosen
Indicates that there is a limitation or constraint on which genres are allowed or applicable in a given context.
-
B.
genreIncludes
Indicates that a broader genre category encompasses or contains a specified subgenre or work as part of its classification.
-
C.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
D.
genreSpecialty
Indicates that an entity specializes in or is particularly associated with a specific genre.
-
E.
legalGenre
Indicates that one entity is classified as a legal genre or category of law-related content for the other 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.