Triple
T34083288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Collingwood |
E874105
|
entity |
| Predicate | marriedInSeriesTo |
P140690
|
FINISHED |
| Object | Peter Munion |
—
|
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: Peter Munion | Statement: [Caroline Collingwood, marriedInSeriesTo, Peter Munion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedInSeriesTo Context triple: [Caroline Collingwood, marriedInSeriesTo, Peter Munion]
-
A.
hasSpouseInTVSeries
chosen
Indicates that one person is the spouse of another person within the context of a specific TV series.
-
B.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
C.
marriedInSeason
Indicates that two entities entered into a marriage during a specified season of the year.
-
D.
romanticPartnerInSeries
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
-
E.
spouseOfProtagonistOf
Indicates that one entity is the spouse (married partner) of the main character (protagonist) of another entity, typically a narrative work.
- 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_69f349a61d448190b74642f325d3eb7a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: May 1, 2026, 1:52 a.m.