Triple
T12951760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille (1936 film) |
E309907
|
entity |
| Predicate | leadMaleActorRole |
P87467
|
FINISHED |
| Object | Robert Taylor as Armand Duval |
—
|
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: Robert Taylor as Armand Duval | Statement: [Camille (1936 film), leadMaleActorRole, Robert Taylor as Armand Duval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadMaleActorRole Context triple: [Camille (1936 film), leadMaleActorRole, Robert Taylor as Armand Duval]
-
A.
originalMaleLeadRole
Indicates that an entity was the first male actor to play a particular leading role in a work or production.
-
B.
maleLeadActor
chosen
Indicates that the subject is the primary male actor in a performance or production.
-
C.
replacesInLeadRole
Indicates that one entity takes over or substitutes for another entity in the primary or leading role within a given context or production.
-
D.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
E.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.