Triple
T10083876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Perron |
E213969
|
entity |
| Predicate | realPersonBehind |
P54368
|
FINISHED |
| Object | character Roger Perron in The Conjuring |
—
|
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: character Roger Perron in The Conjuring | Statement: [Roger Perron, realPersonBehind, character Roger Perron in The Conjuring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realPersonBehind Context triple: [Roger Perron, realPersonBehind, character Roger Perron in The Conjuring]
-
A.
basedOnRealPersonFor
chosen
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
-
B.
realName
Indicates that one entity is the actual, full, or birth name of another entity, which may be known by an alias, nickname, or alternate identity.
-
C.
frontPerson
Indicates that one entity serves as the primary representative, leader, or public face positioned at the forefront in relation to another entity.
-
D.
hasFrontPerson
Indicates that an entity is represented, led, or fronted publicly by a specific person.
-
E.
realityStatus
Indicates the relationship between an entity and its state of existence or authenticity within a given context or world (e.g., real, fictional, hypothetical, simulated).
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04352d081908f676444cd2d2578 |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.