Triple
T34967879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenny Haise |
E1008452
|
entity |
| Predicate | bandFormerNameInFilm |
P61177
|
FINISHED |
| Object | The Oneders |
—
|
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: The Oneders | Statement: [Lenny Haise, bandFormerNameInFilm, The Oneders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bandFormerNameInFilm Context triple: [Lenny Haise, bandFormerNameInFilm, The Oneders]
-
A.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
-
B.
hasOriginalBandNameOf
chosen
Indicates that one entity is the original band name used by another musical group or artist.
-
C.
sungInFilmBy
Indicates that a particular song was vocally performed in a film by a specific person or group.
-
D.
madeFamousByFilm
Indicates that something became widely known or gained significant public recognition as a result of being featured in a film.
-
E.
recordLabelInFilm
Indicates that a particular record label is featured, referenced, or involved within a specific 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.