Triple
T10527589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Real Women Have Curves |
E248345
|
entity |
| Predicate | motherDaughterConflictTheme |
P86907
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Real Women Have Curves, motherDaughterConflictTheme, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motherDaughterConflictTheme Context triple: [Real Women Have Curves, motherDaughterConflictTheme, yes]
-
A.
parentalConflictWith
Indicates a relationship in which two parents are in disagreement, tension, or dispute with each other, often over child-related or family matters.
-
B.
daughters
Indicates that one entity is the female child of another entity.
-
C.
parentalIssue
chosen
Indicates that there is a problem, conflict, or difficulty involving a person's relationship or situation with their parent(s).
-
D.
motherInStory
Indicates that one entity is the mother of another entity within the context of a particular story or narrative.
-
E.
daughterOf
Indicates that one person is the female child (daughter) of another person.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f5ec348190875c8c877e70ba4a |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:29 p.m.