Triple
T33676403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corleone |
E862769
|
entity |
| Predicate | familyMemberCharacter |
P184664
|
FINISHED |
| Object | Vito Corleone |
—
|
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: Vito Corleone | Statement: [Corleone, familyMemberCharacter, Vito Corleone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyMemberCharacter Context triple: [Corleone, familyMemberCharacter, Vito Corleone]
-
A.
portrayedFamilyMemberOf
Indicates that one entity has depicted another entity as a member of their family, typically in a creative or representational context such as art, film, or literature.
-
B.
rocketFamilyMember
Indicates that one entity is a member of the same rocket family or series as another entity, sharing a common design lineage or classification.
-
C.
hasProtagonistFamilyMember
Indicates that a work’s protagonist has a specified individual as a member of their family.
-
D.
storylineFamilyMember
chosen
Indicates that one character is related to another as a family member within the context of a storyline or narrative.
-
E.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
- 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_69f34985885c8190914322f492e04703 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:43 a.m.