Triple
T2182737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Her Majesty the Empress Emerita |
E49081
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michiko |
E4280
|
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: Michiko | Statement: [Her Majesty the Empress Emerita, name, Michiko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michiko Context triple: [Her Majesty the Empress Emerita, name, Michiko]
-
A.
Michiko
chosen
Michiko is the former Empress of Japan and the wife of Emperor Emeritus Akihito, known for being the first commoner to marry into the Japanese imperial family.
-
B.
Totsuko
Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
-
C.
Kazuko
Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
-
D.
Aiko, Princess Toshi
Aiko, Princess Toshi is the only child of Emperor Naruhito and Empress Masako of Japan and a member of the Japanese 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf0d551881909d7f907378e1b2b7 |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5da786e48190896cae8fdcee3d83 |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:45 p.m.