Triple
T985896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vampira |
E21278
|
entity |
| Predicate | inUniverseRole |
P11687
|
FINISHED |
| Object | host of late-night horror movies |
—
|
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: host of late-night horror movies | Statement: [Vampira, inUniverseRole, host of late-night horror movies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseRole Context triple: [Vampira, inUniverseRole, host of late-night horror movies]
-
A.
servesRole
chosen
Indicates that one entity performs, fulfills, or occupies a particular function, position, or responsibility in relation to another entity.
-
B.
definesRole
Indicates that one entity specifies or establishes the role, function, or position of another entity within a given context.
-
C.
hasGlobalRole
Indicates that an entity holds a role or permission set that applies across an entire system or domain, rather than being limited to a specific scope or context.
-
D.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
E.
allianceRole
Indicates the specific function, status, or responsibility an entity holds within an alliance or cooperative partnership.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b496b7308190a9c201244330b784 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.