Triple
T33731248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Armorer |
E864280
|
entity |
| Predicate | stuntDouble |
P40736
|
FINISHED |
| Object | Lauren Mary Kim |
—
|
NE NERFINISHED |
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: Lauren Mary Kim | Statement: [The Armorer, stuntDouble, Lauren Mary Kim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stuntDouble Context triple: [The Armorer, stuntDouble, Lauren Mary Kim]
-
A.
hasStuntDouble
chosen
Indicates that one entity serves as a stunt double who performs dangerous or physically demanding actions on behalf of another entity.
-
B.
stuntPerformerIn
Indicates that one entity serves as a stunt performer in a work, production, or performance associated with another entity.
-
C.
actsInSteadOf
Indicates that one entity performs an action or fulfills a role as a substitute or proxy for another entity.
-
D.
hasDubActor
Indicates that one entity serves as the dubbing voice actor for another entity in a particular work or version.
-
E.
stuntCoordinatorOn
Indicates that one entity serves as the stunt coordinator responsible for designing and overseeing stunts on a particular production or project involving another entity.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb1eeb64819083f6f04633b000f2 |
completed | May 3, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:44 a.m.