Triple
T10471261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jess (Venus) |
E246926
|
entity |
| Predicate | castMemberRelationship |
P74774
|
FINISHED |
| Object | Jodie Whittaker as Jess in Venus |
—
|
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: Jodie Whittaker as Jess in Venus | Statement: [Jess (Venus), castMemberRelationship, Jodie Whittaker as Jess in Venus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: castMemberRelationship Context triple: [Jess (Venus), castMemberRelationship, Jodie Whittaker as Jess in Venus]
-
A.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
B.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
C.
directorSpouseInCast
Indicates that a film’s director is married to someone who appears as a cast member in that same film.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
castMemberWith
chosen
Indicates that one entity is a cast member appearing together with another specified entity in the same production or 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:20 p.m.