Triple
T4824352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michiko Shōda |
E107785
|
entity |
| Predicate | startTimeOfPositionCrownPrincess |
P15467
|
FINISHED |
| Object | 1959-04-10 |
—
|
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: 1959-04-10 | Statement: [Michiko Shōda, startTimeOfPositionCrownPrincess, 1959-04-10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfPositionCrownPrincess Context triple: [Michiko Shōda, startTimeOfPositionCrownPrincess, 1959-04-10]
-
A.
becameCrownPrincessOn
chosen
Indicates the date on which an individual assumed the title and role of crown princess.
-
B.
positionDuringCoronation
Indicates the specific role, title, or office an entity held at the time of a coronation event.
-
C.
crownPosition
Indicates the relative placement or orientation of a crown with respect to another object or reference point.
-
D.
crownPrinceDuringEvent
Indicates that an individual holds the position of crown prince during the time span of a specified event.
-
E.
dateBecamePrincessRoyal
Indicates the specific date on which an individual assumed the title or status of Princess Royal.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.