Triple
T34439950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farrow–Previn family |
E884068
|
entity |
| Predicate | hasChildrenType |
P70217
|
FINISHED |
| Object | adopted children |
—
|
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: adopted children | Statement: [Farrow–Previn family, hasChildrenType, adopted children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChildrenType Context triple: [Farrow–Previn family, hasChildrenType, adopted children]
-
A.
hasChildrenWith
Indicates that two entities share one or more biological or adopted children together.
-
B.
hasDescendantsType
chosen
Indicates that an entity has descendants belonging to a specified type or category.
-
C.
hasSiblingsType
Indicates that the subject has siblings of a specified type or category (e.g., biological, step, half).
-
D.
hasSiblingType
Indicates that one entity has another entity as a sibling, specifying the type or category of that sibling relationship.
-
E.
hasChildrenArea
Indicates that an entity includes or is associated with a designated area intended for children.
- 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: May 1, 2026, 2 a.m.