Triple
T34560184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Scars of Dracula |
E887314
|
entity |
| Predicate | hasDraculaPortrayalBy |
P9616
|
FINISHED |
| Object | Christopher Lee |
—
|
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: Christopher Lee | Statement: [The Scars of Dracula, hasDraculaPortrayalBy, Christopher Lee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDraculaPortrayalBy Context triple: [The Scars of Dracula, hasDraculaPortrayalBy, Christopher Lee]
-
A.
hasHumanCast
Indicates that a work or production features human performers as part of its cast.
-
B.
hasYoungPortrayalOf
Indicates that one entity is a portrayal or depiction of another entity specifically in their younger age or earlier life stage.
-
C.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
D.
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.
-
E.
hasPortrayedRole
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
- 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_69f349d0c4d881908dd0950f5eb9ec0a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72062ad8081909e0a746d7e1734ee |
completed | May 3, 2026, 10:16 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.