Triple
T24226368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byzantium (film) |
E601606
|
entity |
| Predicate | hasTypeOfVampireLore |
P113104
|
FINISHED |
| Object | non-traditional vampire mythology |
—
|
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: non-traditional vampire mythology | Statement: [Byzantium (film), hasTypeOfVampireLore, non-traditional vampire mythology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfVampireLore Context triple: [Byzantium (film), hasTypeOfVampireLore, non-traditional vampire mythology]
-
A.
vampireType
Indicates that one entity is classified as a specific type or category of vampire in relation to another entity.
-
B.
hasVampireCharacter
Indicates that an entity includes or features at least one character who is a vampire.
-
C.
hasVampireMaker
Indicates that one entity is the creator or sire who turned another entity into a vampire.
-
D.
portraysVampiresAs
chosen
Indicates how something represents or depicts vampires, especially in terms of their nature, traits, or role.
-
E.
hasSupernaturalStatus
Indicates that an entity possesses a status, condition, or role that is beyond or outside normal natural laws (e.g., divine, magical, or otherwise supernatural).
- 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_69e29537ca548190b94a37ebe1977caf |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f287dffa6c81908564b74dbfae780b |
completed | April 29, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, midnight