Triple
T21867146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Temple Canfield |
E539909
|
entity |
| Predicate | startTimeOfMarriageToLauraCharteris |
P145975
|
FINISHED |
| Object | 1960 |
—
|
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: 1960 | Statement: [Michael Temple Canfield, startTimeOfMarriageToLauraCharteris, 1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfMarriageToLauraCharteris Context triple: [Michael Temple Canfield, startTimeOfMarriageToLauraCharteris, 1960]
-
A.
marriageStartTimeWithCharlieBrooks
Indicates the time at which a marriage involving Charlie Brooks began.
-
B.
marriageStartDateWithRobertCarr
Indicates the date on which an entity’s marriage to Robert Carr began.
-
C.
marriageStartTimeWithCharityHallett
Indicates the date and time when the subject’s marriage to Charity Hallett began.
-
D.
marriageStartTimeWithRossKemp
Indicates the time at which a marriage involving Ross Kemp officially began.
-
E.
marriageStartTimeWithCarolOrchard
Indicates the time at which a marriage to Carol Orchard begins.
- F. None of above. chosen
Provenance (4 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f331c55c8190b73cb5aec3378a9e |
completed | April 28, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 6:57 p.m.