Triple
T25384090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris Pressagh |
E631472
|
entity |
| Predicate | marriageSequenceForBillyConnolly |
P160861
|
FINISHED |
| Object | first wife |
—
|
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: first wife | Statement: [Iris Pressagh, marriageSequenceForBillyConnolly, first wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageSequenceForBillyConnolly Context triple: [Iris Pressagh, marriageSequenceForBillyConnolly, first wife]
-
A.
marriageOrderWithBillyBobThornton
Indicates the chronological position in which an entity was married to Billy Bob Thornton relative to his other spouses.
-
B.
marriageOrderRelativeToNoelEdmonds
Indicates the relative chronological position of a marriage event in comparison to Noel Edmonds’ marriage timeline.
-
C.
marriageSequenceWithLarryKing
Indicates the ordered position of a marriage within the sequence of all marriages involving Larry King.
-
D.
marriageOrderWithTonyBennett
Indicates the ordinal position in which an entity married Tony Bennett relative to his other spouses.
-
E.
marriageSequenceToHussein
Indicates that an entity enters into a marriage with Hussein at a specific point or order within a sequence of marriages.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f60ac643108190ae81561267155791 |
completed | May 2, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f606c15af88190958856a9e467b826 |
completed | May 2, 2026, 2:14 p.m. |
Created at: April 21, 2026, 1:46 p.m.