Triple
T28799263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stacey Colbert |
E727183
|
entity |
| Predicate | hasSpouseInPlot |
P30304
|
FINISHED |
| Object | Ned Dorsey |
—
|
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: Ned Dorsey | Statement: [Stacey Colbert, hasSpouseInPlot, Ned Dorsey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseInPlot Context triple: [Stacey Colbert, hasSpouseInPlot, Ned Dorsey]
-
A.
hasSpouseInStory
chosen
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
B.
hasMarriagePlot
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
C.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
D.
hasJealousHusbandCharacter
Indicates that an entity includes or involves a husband character who experiences or expresses jealousy in the context of the relationship or narrative.
-
E.
hasSpouseInTVSeries
Indicates that one person is the spouse of another person within the context of a specific TV series.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: April 28, 2026, 6:26 a.m.