Triple
T7909697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agyness Deyn |
E183665
|
entity |
| Predicate | marriageToJoelMcAndrewStart |
P79720
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Agyness Deyn, marriageToJoelMcAndrewStart, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageToJoelMcAndrewStart Context triple: [Agyness Deyn, marriageToJoelMcAndrewStart, 2016]
-
A.
marriageStartTimeWithRossKemp
Indicates the time at which a marriage involving Ross Kemp officially began.
-
B.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
C.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
-
D.
marriageStartTimeWithCharlieBrooks
Indicates the time at which a marriage involving Charlie Brooks began.
-
E.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a5db9508190bbe92673ef5a7861 |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:04 p.m.