Triple
T12250794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cindy McCain |
E291964
|
entity |
| Predicate | startTime_spouse_John_McCain |
P103726
|
FINISHED |
| Object | 1980 |
—
|
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: 1980 | Statement: [Cindy McCain, startTime_spouse_John_McCain, 1980]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime_spouse_John_McCain Context triple: [Cindy McCain, startTime_spouse_John_McCain, 1980]
-
A.
spousePositionHeldStartTime
Indicates the date and time when a spouse first began holding a particular position or office.
-
B.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
C.
runningMateOfJebBush
Indicates that the subject was the vice-presidential running mate of Jeb Bush in an election.
-
D.
spouseNumberOfTermsInOffice
Indicates the number of distinct terms in office that the spouse of the referenced entity has served.
-
E.
endTimeOfSpouse_J. Howard Marshall
Indicates the time at which the marital relationship with J. Howard Marshall ended.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d38ee10819093ed41d2954bf4ef |
completed | April 10, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69d91c46dcd88190a263db30804bff36 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d91d3654208190a2e0487dfa1d54da |
completed | April 10, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:52 p.m.