Triple
T6053974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshiko Ikeda |
E134861
|
entity |
| Predicate | firstLadyTermApproximateStart |
P67988
|
FINISHED |
| Object | early 1960s |
—
|
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: early 1960s | Statement: [Yoshiko Ikeda, firstLadyTermApproximateStart, early 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLadyTermApproximateStart Context triple: [Yoshiko Ikeda, firstLadyTermApproximateStart, early 1960s]
-
A.
servedAsFirstLadyOfTheUnitedStatesFrom
Indicates that a person held the role of First Lady of the United States during a specified time period.
-
B.
precededAsFirstLadyOfTheUnitedStatesBy
Indicates that one person served as First Lady of the United States immediately before another person.
-
C.
hasFirstLadyMember
Indicates that an entity has, as a member, a woman who holds the role or title of First Lady.
-
D.
succeededAsFirstLadyOfTheUnitedStatesBy
Indicates that one person ceased serving as First Lady of the United States and was directly followed in that role by another specific person.
-
E.
startTimeAsFirstLadyOfCalifornia
Indicates the date and time when an individual first assumed the role of First Lady of California.
- 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_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. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:09 p.m.