Triple
T10293265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara "Sway" Wayland |
E241415
|
entity |
| Predicate | basedInWorkType |
P86785
|
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: [Sara "Sway" Wayland, basedInWorkType, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedInWorkType Context triple: [Sara "Sway" Wayland, basedInWorkType, feature film]
-
A.
associatedWorkType
chosen
Indicates the type or category of work with which an entity is associated (e.g., publication, artwork, performance).
-
B.
basedOnWorkTitle
Indicates that something is derived from, adapted from, or otherwise created based on a work identified by its title.
-
C.
originallyFromWorkType
Indicates that one entity was derived, adapted, or sourced from an original work of a specified type (e.g., book, film, artwork).
-
D.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
E.
basedOnWorkAdaptedTo
Indicates that one work is derived from and adapted based on the content, story, or elements of another pre-existing work.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d46fb08190b7694290692e47dc |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.