Triple
T23605146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The House of Yes |
E582868
|
entity |
| Predicate | protagonistObsession |
P49999
|
FINISHED |
| Object | Jacqueline Kennedy Onassis |
—
|
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: Jacqueline Kennedy Onassis | Statement: [The House of Yes, protagonistObsession, Jacqueline Kennedy Onassis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistObsession Context triple: [The House of Yes, protagonistObsession, Jacqueline Kennedy Onassis]
-
A.
obsessionWith
chosen
Indicates an intense, persistent, and often overwhelming preoccupation or fixation that one entity has toward another entity or object.
-
B.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
protagonistAction
Indicates that the referenced entity performs the central or primary action associated with the main character in a narrative or scenario.
-
D.
protagonistMust
Indicates that a particular entity is required to serve as the main character or central focus within a narrative or scenario.
-
E.
protagonistLover
Indicates that one entity is the romantic partner or love interest of the story’s protagonist.
- 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0ef32b481909590a1a5853df5d9 |
completed | April 29, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:44 p.m.