Triple
T28755864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrissie Mullen |
E731668
|
entity |
| Predicate | spouseGenreAssociation |
P44007
|
FINISHED |
| Object | rock music |
—
|
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: rock music | Statement: [Chrissie Mullen, spouseGenreAssociation, rock music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseGenreAssociation Context triple: [Chrissie Mullen, spouseGenreAssociation, rock music]
-
A.
genreAssociatedWithSpouse
chosen
Indicates that a particular genre is associated with, or characterizes, the spouse of the referenced entity.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
spouseAppearsIn
Indicates that the spouse of a given person appears or is featured in a specified work, context, or setting.
-
D.
hasSpouseActorsInLeads
Indicates that the primary leading roles in a work are performed by actors who are spouses of each other.
-
E.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
- 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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 28, 2026, 6:09 a.m.