Triple
T1561502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshihito |
E33333
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Yanagiwara Naruko |
E133902
|
NE 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: Yanagiwara Naruko | Statement: [Yoshihito, mother, Yanagiwara Naruko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yanagiwara Naruko Context triple: [Yoshihito, mother, Yanagiwara Naruko]
-
A.
Yanagihara Naruko
chosen
Yanagihara Naruko was a Japanese noblewoman and concubine of Emperor Meiji, best known as the mother of Emperor Taishō.
-
B.
Itō Sukeyuki
Itō Sukeyuki was a Japanese admiral who became prominent as a leading naval commander during Japan’s early modern wars and the country’s rise as a maritime power.
-
C.
Yodo-dono
Yodo-dono was a prominent Japanese noblewoman and political figure of the late Sengoku period, best known as Toyotomi Hideyoshi’s consort and the mother of his heir, Toyotomi Hideyori.
-
D.
Shigeko
Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
-
E.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9088710a881909a1226e4b54311b8 |
completed | March 5, 2026, 4:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb90e16081908d70df182b7efb8a |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:27 p.m.