Triple
T34967878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenny Haise |
E1008452
|
entity |
| Predicate | bandNameInFilm |
P182147
|
FINISHED |
| Object | The Wonders |
—
|
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 Wonders | Statement: [Lenny Haise, bandNameInFilm, The Wonders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bandNameInFilm Context triple: [Lenny Haise, bandNameInFilm, The Wonders]
-
A.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
-
B.
bondActorInFilm
Indicates that the person is an actor who has portrayed the character James Bond in a film.
-
C.
recordLabelInFilm
Indicates that a particular record label is featured, referenced, or involved within a specific film.
-
D.
hasStageNameInFilm
Indicates that an individual is credited or referred to by a particular stage name in a specific film.
-
E.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
- F. None of above. chosen
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_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. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.