Triple
T8034860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōjun Kōgō |
E187079
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nagako |
E471498
|
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: Nagako | Statement: [Kōjun Kōgō, givenName, Nagako]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagako Context triple: [Kōjun Kōgō, givenName, Nagako]
-
A.
Nagako
chosen
Nagako, better known as Empress Kōjun, was the long-serving consort of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito of Japan.
-
B.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
-
C.
Chikako
Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
-
D.
Masako
Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
-
E.
Shigeko
Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef50f4c8190a895ac301f182734 |
completed | March 31, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd340abffc8190bbc17aa9b775a9cb |
completed | April 1, 2026, 3:04 p.m. |
Created at: March 30, 2026, 5:22 p.m.