Triple
T38208902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Death Kiss |
E1009282
|
entity |
| Predicate | starredInPreviously |
P10843
|
FINISHED |
| Object | Bela Lugosi |
—
|
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: Bela Lugosi | Statement: [The Death Kiss, starredInPreviously, Bela Lugosi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starredInPreviously Context triple: [The Death Kiss, starredInPreviously, Bela Lugosi]
-
A.
starredActorWith
Indicates that one entity participated as an actor in a production together with another specified actor.
-
B.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
C.
alsoPlayedIn
chosen
Indicates that an entity (such as a person or performer) participated or appeared in another work, production, or context in addition to the one already referenced.
-
D.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
E.
producedFilmStarring
Indicates that a person or company produced a film in which a specified actor or set of actors starred.
- 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_69f76dc94fcc8190bd2f55e81f9d6527 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:30 p.m.