Triple
T28279240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivián Francis Bulkeley-Johnson |
E713093
|
entity |
| Predicate | saidToBeTheSecondHusbandOf |
P81984
|
FINISHED |
| Object | Cornelia Stuyvesant Vanderbilt |
—
|
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: Cornelia Stuyvesant Vanderbilt | Statement: [Vivián Francis Bulkeley-Johnson, saidToBeTheSecondHusbandOf, Cornelia Stuyvesant Vanderbilt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: saidToBeTheSecondHusbandOf Context triple: [Vivián Francis Bulkeley-Johnson, saidToBeTheSecondHusbandOf, Cornelia Stuyvesant Vanderbilt]
-
A.
secondWifeOf
Indicates that one person is the second spouse (by order of marriage) of another person.
-
B.
secondHusbandInstanceOf
chosen
Indicates that one person is the second husband of another person in a sequence of marital relationships.
-
C.
givenToSecondHusbandBy
Indicates that something was transferred or bestowed upon a person by their second husband.
-
D.
subsequentSpouse
Indicates that one person is a later spouse of another, following a previous marriage involving at least one of them.
-
E.
allegedSpouseOf
Indicates a relationship where one person is claimed or reported to be the spouse of another, but the marital status is not legally or definitively confirmed.
- 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_69efb52275788190ae5181ccebef18ce |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6444debc88190a2799fedc421013a |
completed | May 2, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:21 p.m.