Triple
T6896727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 佳子内親王 |
E159387
|
entity |
| Predicate | 成年年齢到達 |
P40917
|
FINISHED |
| Object | 2014年に成年皇族となった |
—
|
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: 2014年に成年皇族となった | Statement: [佳子内親王, 成年年齢到達, 2014年に成年皇族となった]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 成年年齢到達 Context triple: [佳子内親王, 成年年齢到達, 2014年に成年皇族となった]
-
A.
canAgeFor
Indicates that one entity is capable of undergoing an aging or maturation process for the benefit, use, or context of another entity.
-
B.
cameOfAge
chosen
Indicates that an entity reached the age or stage of maturity at which it is considered an adult or fully responsible.
-
C.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
D.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
E.
typicallyIssuedAtAge
Indicates the age at which something is most commonly or customarily issued to an individual.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d95ae3f88190b7f5d440f90ae9f9 |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:24 p.m.