Triple
T35180876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birdland |
E1015842
|
entity |
| Predicate | starredInFirstProduction |
P5563
|
FINISHED |
| Object | Andrew Scott |
—
|
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: Andrew Scott | Statement: [Birdland, starredInFirstProduction, Andrew Scott]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starredInFirstProduction Context triple: [Birdland, starredInFirstProduction, Andrew Scott]
-
A.
stageDebutWorkPremiereYear
Indicates the year in which a work was first premiered or debuted on stage.
-
B.
starredActor
chosen
Indicates that an actor performed a leading or significant role in a particular production or work.
-
C.
starredActorWith
Indicates that one entity participated as an actor in a production together with another specified actor.
-
D.
producedFilmStarring
Indicates that a person or company produced a film in which a specified actor or set of actors starred.
-
E.
hasFirstFilm
Indicates the specific film that is recognized as the first film associated with an entity (such as a person, series, or franchise).
- 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d7b32f88190a5811a1ad85a90a2 |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.