Triple
T3297560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Michiko |
E69251
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Shōda |
E34837
|
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: Shōda | Statement: [Empress Michiko, familyName, Shōda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shōda Context triple: [Empress Michiko, familyName, Shōda]
-
A.
Shōda
chosen
Shōda is a Japanese surname notably borne by Michiko Shōda, who became Empress Michiko of Japan.
-
B.
Gotō
Gotō is a Japanese surname borne by various notable figures in politics, business, and the arts.
-
C.
Chō
Chō is a Japanese surname borne by various notable individuals across fields such as the military, arts, and entertainment.
-
D.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
E.
Tanaka
Tanaka is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a2f4708190821edb9700f62d2f |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3d35c448190a4ca50ae31639e65 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.