Triple
T33144534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Sussex Vampire |
E848253
|
entity |
| Predicate | hasVampireMotif |
P64901
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Adventure of the Sussex Vampire, hasVampireMotif, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVampireMotif Context triple: [The Adventure of the Sussex Vampire, hasVampireMotif, yes]
-
A.
hasVampireCharacter
Indicates that an entity includes or features at least one character who is a vampire.
-
B.
hasVampireMaker
Indicates that one entity is the creator or sire who turned another entity into a vampire.
-
C.
vampireType
Indicates that one entity is classified as a specific type or category of vampire in relation to another entity.
-
D.
portraysVampiresAs
Indicates how something represents or depicts vampires, especially in terms of their nature, traits, or role.
-
E.
hasHorrorElements
chosen
Indicates that something contains features, themes, or stylistic aspects characteristic of the horror genre.
- 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_69f3495a458c8190a1d34b237ba0be3f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:28 a.m.