Triple
T33460733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katherine |
E856906
|
entity |
| Predicate | guardianInFilm |
P175491
|
FINISHED |
| Object | Evelyn Mulwray |
—
|
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: Evelyn Mulwray | Statement: [Katherine, guardianInFilm, Evelyn Mulwray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guardianInFilm Context triple: [Katherine, guardianInFilm, Evelyn Mulwray]
-
A.
guardian
Indicates a protective or custodial relationship in which one entity is responsible for the care, safety, or oversight of another.
-
B.
guardianInPlot
chosen
Indicates that one entity serves as a guardian or protector of another entity within the context of a specific plot or storyline.
-
C.
guardianStatuesRole
Indicates the role or function that guardian statues perform in relation to the entities or places they protect.
-
D.
hasGuardianCharacter
Indicates that one entity serves as a guardian or protective character for another entity.
-
E.
leadActorPlaysBodyguard
Indicates that the lead actor portrays the role of a bodyguard.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:37 a.m.