Triple
T35371854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandra Bullock as Sarah Ashburn |
E1021792
|
entity |
| Predicate | partOfFranchiseType |
P202477
|
FINISHED |
| Object | standalone 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: standalone film | Statement: [Sandra Bullock as Sarah Ashburn, partOfFranchiseType, standalone film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfFranchiseType Context triple: [Sandra Bullock as Sarah Ashburn, partOfFranchiseType, standalone film]
-
A.
partOfFranchiseLineage
Indicates that one entity belongs to, or is derived from, the same overarching franchise lineage as another entity, reflecting continuity within a shared franchise.
-
B.
partOfFranchiseOrAdaptations
Indicates that one work belongs to the same franchise as another work or is an adaptation derived from it.
-
C.
partOfFranchiseOrigin
Indicates that one entity originates from, or is derived as part of, a larger franchise associated with another entity.
-
D.
partOfFranchiseWithWork
Indicates that one work belongs to, or is included within, the same franchise as another work.
-
E.
includedInFranchise
Indicates that an entity is part of, or belongs to, a larger franchise or franchise series.
- F. None of above. chosen
Provenance (4 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
| PDg | Predicate description generation | batch_6a00867f57a48190a4205a859a268998 |
completed | May 10, 2026, 1:22 p.m. |
Created at: May 3, 2026, 4:03 p.m.