Triple
T9653286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vampirina |
E233386
|
entity |
| Predicate | featuresSupernaturalBeings |
P83317
|
FINISHED |
| Object | 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: vampires | Statement: [Vampirina, featuresSupernaturalBeings, vampires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSupernaturalBeings Context triple: [Vampirina, featuresSupernaturalBeings, vampires]
-
A.
containsSupernaturalElement
Indicates that the subject involves or features a supernatural, magical, or otherworldly element beyond normal natural laws.
-
B.
featuresCreatureOrLegend
chosen
Indicates that something includes, depicts, or prominently involves a particular creature or legendary being.
-
C.
featuresMonster
Indicates that something includes or prominently presents a monster as part of its content or composition.
-
D.
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).
-
E.
hasSupernaturalPerceptionOf
Indicates that one entity possesses a supernatural or extrasensory awareness, insight, or perception specifically directed toward another entity.
- 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bb26b748190bc32e2003829b0ec |
completed | April 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b0263081908cf6df3eb07d71b0 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:13 p.m.