Triple
T25384866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deacon Frost |
E631493
|
entity |
| Predicate | filmGoal |
P158479
|
FINISHED |
| Object | ruling over humans and vampires |
—
|
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: ruling over humans and vampires | Statement: [Deacon Frost, filmGoal, ruling over humans and vampires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmGoal Context triple: [Deacon Frost, filmGoal, ruling over humans and vampires]
-
A.
filmGoal
chosen
Indicates that a film is created with the purpose, objective, or intended outcome of achieving a particular goal.
-
B.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or context.
-
C.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
D.
filmGauge
Indicates the specific width or size of the film stock used in a motion picture or photographic recording.
-
E.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
- 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_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_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:46 p.m.