Triple
T26428966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miffy Englefield |
E664448
|
entity |
| Predicate | hasRelativeOnScreen |
P141370
|
FINISHED |
| Object | Jude Law’s character as father of Sophie |
—
|
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: Jude Law’s character as father of Sophie | Statement: [Miffy Englefield, hasRelativeOnScreen, Jude Law’s character as father of Sophie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeOnScreen Context triple: [Miffy Englefield, hasRelativeOnScreen, Jude Law’s character as father of Sophie]
-
A.
hasOnScreenRelative
chosen
Indicates that one entity has a family member who appears or is depicted on screen in relation to it.
-
B.
hasOnScreenLocationType
Indicates that an entity’s location, as presented or visible on a screen, is of a specified type or category.
-
C.
hasOnScreenDynamic
Indicates that one entity displays or presents another entity as a changing or interactive element on a screen.
-
D.
hasOnScreenNeighbour
Indicates that one entity appears adjacent to another entity within the same on-screen context or display.
-
E.
hasScreenLocation
Indicates that an entity is associated with a specific position or region on a screen or display surface.
- 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_69ee883ad6a4819088f918e76122d690 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: April 26, 2026, 11:47 p.m.