Triple
T18820649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Helsing (2004 film) |
E460252
|
entity |
| Predicate | portraysFictionalMonster |
P18264
|
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: [Van Helsing (2004 film), portraysFictionalMonster, vampires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysFictionalMonster Context triple: [Van Helsing (2004 film), portraysFictionalMonster, vampires]
-
A.
portraysFictionalEntity
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
-
B.
featuresMonster
chosen
Indicates that something includes or prominently presents a monster as part of its content or composition.
-
C.
portraysFictionalCoven
Indicates that an entity depicts or represents a fictional coven, typically in a narrative or artistic context.
-
D.
portraysFictionalized
Indicates that one entity represents or depicts another entity in a fictionalized or altered manner, rather than as a strictly accurate portrayal.
-
E.
portraysFictionalUniverse
Indicates that one entity depicts, represents, or presents the fictional universe in which another entity is set.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6b9be988190b5e3804c39dc7dd9 |
completed | April 20, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:55 a.m.