Triple
T4555903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyra Sedgwick as Brenda Leigh Johnson |
E120475
|
entity |
| Predicate | notableThemeInArc |
P7671
|
FINISHED |
| Object | balancingPersonalLifeAndCareer |
—
|
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: balancingPersonalLifeAndCareer | Statement: [Kyra Sedgwick as Brenda Leigh Johnson, notableThemeInArc, balancingPersonalLifeAndCareer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableThemeInArc Context triple: [Kyra Sedgwick as Brenda Leigh Johnson, notableThemeInArc, balancingPersonalLifeAndCareer]
-
A.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
B.
notableStoryArc
Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
-
C.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
D.
themedAs
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
-
E.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic context.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd5814f56c8190a65f61f6148b7e5a |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.