Triple
T6053972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshiko Ikeda |
E134861
|
entity |
| Predicate | spouseTermStartAsPrimeMinister |
P37616
|
FINISHED |
| Object | 1960 |
—
|
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: 1960 | Statement: [Yoshiko Ikeda, spouseTermStartAsPrimeMinister, 1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseTermStartAsPrimeMinister Context triple: [Yoshiko Ikeda, spouseTermStartAsPrimeMinister, 1960]
-
A.
spousePositionHeldStartTime
chosen
Indicates the date and time when a spouse first began holding a particular position or office.
-
B.
spouseStartTime
Indicates the point in time when two individuals began their spousal (marriage) relationship.
-
C.
spouseOfSince
Indicates that two individuals are spouses and specifies the date or time from which their marital relationship has been in effect.
-
D.
spouseOfCountry
Indicates that an entity is the spouse or marital partner of a person who is associated with, represents, or is from a specified country.
-
E.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05708fda48190ad3d1860969ebb6a |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:09 p.m.