Triple
T20819030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Connelly as Betty Ross |
E512521
|
entity |
| Predicate | hasFatherDaughterConflict |
P141953
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jennifer Connelly as Betty Ross, hasFatherDaughterConflict, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFatherDaughterConflict Context triple: [Jennifer Connelly as Betty Ross, hasFatherDaughterConflict, true]
-
A.
raisesAsDaughter
Indicates that one entity brings up and cares for another as their daughter, in a parental role.
-
B.
parentalConflictWith
Indicates a relationship in which two parents are in disagreement, tension, or dispute with each other, often over child-related or family matters.
-
C.
notableFamilyConflict
Indicates a significant, recognized dispute or ongoing tension between members of the same family.
-
D.
oftenHasFather
Indicates that the subject entity frequently or typically has a father relationship to the specified object entity.
-
E.
hasDaughters
Indicates that one entity is the parent of one or more female child entities (daughters).
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f5b1e08190a9c26f76bd544b68 |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:41 p.m.