Triple
T25384865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deacon Frost |
E631493
|
entity |
| Predicate | filmGoal |
P158479
|
FINISHED |
| Object | overthrowing the vampire pureblood elders |
—
|
LITERAL FINISHED |
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: overthrowing the vampire pureblood elders | Statement: [Deacon Frost, filmGoal, overthrowing the vampire pureblood elders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmGoal Context triple: [Deacon Frost, filmGoal, overthrowing the vampire pureblood elders]
-
A.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
B.
filmGauge
Indicates the specific width or size of the film stock used in a motion picture or photographic recording.
-
C.
filmProject
Indicates a relationship where an entity is involved in or associated with a specific film production project.
-
D.
filmContent
Indicates that one entity is the substantive material or subject matter contained within a film.
-
E.
filmWon
Indicates that a film has received or been awarded a particular prize, honor, or recognition.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f5656795248190a732c8596a0e740d |
completed | May 2, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:46 p.m.