Triple
T6222418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dexter |
E139146
|
entity |
| Predicate | protagonistSecretIdentity |
P42867
|
FINISHED |
| Object | vigilante serial killer |
—
|
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: vigilante serial killer | Statement: [Dexter, protagonistSecretIdentity, vigilante serial killer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistSecretIdentity Context triple: [Dexter, protagonistSecretIdentity, vigilante serial killer]
-
A.
hasSecretIdentity
chosen
Indicates that an entity possesses an alternate, hidden identity that is not publicly known.
-
B.
knowsSecretIdentityOf
Indicates that one entity is aware of the hidden or private true identity of another entity.
-
C.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
D.
protagonistAlsoKnownAs
Indicates that an entity serving as a protagonist is alternatively referred to by another name or alias.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062bddb688190add53172a7445d01 |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.