Triple
T19076531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Todd Casey |
E466917
|
entity |
| Predicate | typeOfCreativeWorkContributedTo |
P45535
|
FINISHED |
| Object | feature film |
—
|
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 film | Statement: [Todd Casey, typeOfCreativeWorkContributedTo, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCreativeWorkContributedTo Context triple: [Todd Casey, typeOfCreativeWorkContributedTo, feature film]
-
A.
genreOfWorkContributedTo
Indicates that an entity contributed to a work belonging to a specified genre.
-
B.
workTypeContributedTo
chosen
Indicates that an entity contributed to the creation, development, or production of a particular type of work.
-
C.
hasPartInCreativeOutput
Indicates that an entity contributed a component, role, or involvement to the creation or production of a particular creative work.
-
D.
creativeWorkType
Indicates the specific category or form of a creative work (such as book, movie, painting, or song) that characterizes the relationship.
-
E.
subjectOfWorkBy
Indicates that one entity is the main topic or focus of a work (such as a book, article, or artwork) created by 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e49c7c8190b6ce7b918086b23c |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.