Triple
T23873356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mildred Helen Jones |
E592788
|
entity |
| Predicate | marriedToPositionHeldOfSpouse |
P26554
|
FINISHED |
| Object | Governor of Ohio |
—
|
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: Governor of Ohio | Statement: [Mildred Helen Jones, marriedToPositionHeldOfSpouse, Governor of Ohio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToPositionHeldOfSpouse Context triple: [Mildred Helen Jones, marriedToPositionHeldOfSpouse, Governor of Ohio]
-
A.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
B.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
-
C.
marriedToPolitician
Indicates that a person is married to someone who holds or has held a political office or role.
-
D.
spouseOffice
chosen
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
E.
spouseOfOfficeHolderJurisdiction
Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cbff91788190b7aabe285014b873 |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:14 p.m.