Triple
T25893179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lowe Files |
E652390
|
entity |
| Predicate | hasMainCastFamilyRelationship |
P185617
|
FINISHED |
| Object | father and sons |
—
|
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: father and sons | Statement: [The Lowe Files, hasMainCastFamilyRelationship, father and sons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainCastFamilyRelationship Context triple: [The Lowe Files, hasMainCastFamilyRelationship, father and sons]
-
A.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
B.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
C.
hasProtagonistFamilyMember
Indicates that a work’s protagonist has a specified individual as a member of their family.
-
D.
hasFictionalFamily
Indicates that an entity is associated with a family that exists only within a fictional or imaginary context.
-
E.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
- F. None of above. chosen
Provenance (4 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_69e7ab3c6cc081908de59bfcc28ec19d |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: April 22, 2026, 8:22 a.m.