Triple
T25357581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Medicine Man (1930 film) |
E635865
|
entity |
| Predicate | featuresSilentEraStarInTalkingRole |
P64464
|
FINISHED |
| Object | Betty Bronson |
—
|
NE NERFINISHED |
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: Betty Bronson | Statement: [The Medicine Man (1930 film), featuresSilentEraStarInTalkingRole, Betty Bronson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSilentEraStarInTalkingRole Context triple: [The Medicine Man (1930 film), featuresSilentEraStarInTalkingRole, Betty Bronson]
-
A.
featuresSilentEraPerformer
chosen
Indicates that the subject includes or showcases a performer who was active during the silent film era.
-
B.
speaksInFilm
Indicates that a person or character provides spoken dialogue or voice work within a particular film.
-
C.
sungInFilmBy
Indicates that a particular song was vocally performed in a film by a specific person or group.
-
D.
characterInFilmReleasedIn
Indicates that a character appears in a film that was released in a specified year or time period.
-
E.
madeFamousByFilm
Indicates that something became widely known or gained significant public recognition as a result of being featured in a film.
- 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_69e75a9b7cf481909f2dcdfb37d95ca7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 21, 2026, 1:36 p.m.