Triple
T30470403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Demi Moore pregnancy portrait for Vanity Fair (1991) |
E775275
|
entity |
| Predicate | subjectChildExpected |
P181759
|
FINISHED |
| Object | Scout LaRue Willis |
—
|
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: Scout LaRue Willis | Statement: [Demi Moore pregnancy portrait for Vanity Fair (1991), subjectChildExpected, Scout LaRue Willis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectChildExpected Context triple: [Demi Moore pregnancy portrait for Vanity Fair (1991), subjectChildExpected, Scout LaRue Willis]
-
A.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
B.
childIs
Indicates that one entity is the child (offspring or subordinate descendant) of another entity.
-
C.
asksChildrenTo
Indicates that one entity requests or directs children to perform an action or respond in some way.
-
D.
raisesChildrenIn
Indicates that an entity is responsible for bringing up or caring for children within a particular place or environment.
-
E.
childRepresents
Indicates that a child entity serves as a representation, proxy, or stand-in for another entity in some context or structure.
- 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_69f2249622a48190b1fae2e3e4ee958a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7824dc3f0819092a5102895b4a478 |
completed | May 3, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f7817c79e081908e685c48165e086b |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 29, 2026, 8:11 p.m.