Triple
T32328978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Boy Like That / I Have a Love |
E825994
|
entity |
| Predicate | 1961FilmSingingVoiceOfMaria |
P158643
|
FINISHED |
| Object | Marni Nixon |
—
|
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: Marni Nixon | Statement: [A Boy Like That / I Have a Love, 1961FilmSingingVoiceOfMaria, Marni Nixon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 1961FilmSingingVoiceOfMaria Context triple: [A Boy Like That / I Have a Love, 1961FilmSingingVoiceOfMaria, Marni Nixon]
-
A.
2021FilmPerformerOfAnita
Indicates that an entity performed the role or character named Anita in a film released in 2021.
-
B.
portrayedIn1953FilmBy
Indicates that an entity (typically a person or character) was depicted or played by another entity in a film released in the year 1953.
-
C.
MarilynMonroeRoleType
Indicates the type or category of role associated with Marilyn Monroe in a given context.
-
D.
sungInFilmBy
chosen
Indicates that a particular song was vocally performed in a film by a specific person or group.
-
E.
sopranoRolePerformed
Indicates that an entity has performed a role written for a soprano voice in a musical or operatic 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_69f34912d0c48190bba75770660320e9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:47 a.m.