Triple
T12415126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Cyrene Burch Breckinridge |
E296615
|
entity |
| Predicate | marriedToVicePresident |
P104993
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mary Cyrene Burch Breckinridge, marriedToVicePresident, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToVicePresident Context triple: [Mary Cyrene Burch Breckinridge, marriedToVicePresident, true]
-
A.
marriedToUSPresident
Indicates being legally married to an individual who holds or has held the office of President of the United States.
-
B.
marriedToAFormerFirstLadyOfTheUnitedStates
Indicates that a person is or was married to someone who previously held the role of First Lady of the United States.
-
C.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
D.
marriedToHeadOfGovernmentOf
Indicates that one entity is the spouse of the person who holds the position of head of government of the other entity.
-
E.
precededAsFirstLadyOfTheUnitedStatesBy
Indicates that one person served as First Lady of the United States immediately before another person.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e15f21c8190831c9562ffdd4fda |
completed | April 10, 2026, 7:23 p.m. |
Created at: April 8, 2026, 9:55 p.m.