Triple
T38192667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laddie |
E1005513
|
entity |
| Predicate | featureActorInProminentRole |
P163897
|
FINISHED |
| Object | Virginia Weidler |
E306290
|
NE 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: Virginia Weidler | Statement: [Laddie, featureActorInProminentRole, Virginia Weidler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureActorInProminentRole Context triple: [Laddie, featureActorInProminentRole, Virginia Weidler]
-
A.
leadRoleActor
Indicates that an actor performs a leading or principal role in a work or production.
-
B.
prominentAppearanceFilm
chosen
Indicates that an entity has a major or highly visible role or presence in a particular film.
-
C.
majorActor
Indicates that the subject is a primary or leading participant in the action, event, or production involving the object.
-
D.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
E.
notableCastFeature
Indicates that a cast member has a distinctive or noteworthy characteristic, role, or attribute that is especially significant in the context of the production.
- F. None of above.
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_69f76dbd22f48190940318cea061e8bb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a7ab319ec04819095ea5ba31cf955d1 |
completed | Aug. 11, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:29 p.m.