Triple
T26121043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megan Wallace-Cunningham |
E658967
|
entity |
| Predicate | marriageOrderToSpouse |
P4764
|
FINISHED |
| Object | third wife of Craig Ferguson |
—
|
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: third wife of Craig Ferguson | Statement: [Megan Wallace-Cunningham, marriageOrderToSpouse, third wife of Craig Ferguson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageOrderToSpouse Context triple: [Megan Wallace-Cunningham, marriageOrderToSpouse, third wife of Craig Ferguson]
-
A.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
motherSpouseOrder
Indicates that the subject is the spouse of the object’s mother, with an ordering or ranking among multiple such spouses.
-
C.
hasParentMarriageOrder
Indicates the sequential order of a person’s parents’ marriage relative to any other marriages those parents may have had.
-
D.
predecessorInMaoMarriageOrder
Indicates that one person is immediately earlier than another in the ordered sequence of spouses within a Mao-style marriage arrangement.
-
E.
marriedToRank
Indicates that one entity is married to another entity who holds a specific rank or position.
- 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_69ee5bc2b2948190b458ad3f580af779 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 26, 2026, 8:08 p.m.