Triple
T3107527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itō Sukeyuki |
E64868
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Itō Sukeyuki |
E64868
|
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: Itō Sukeyuki | Statement: [Itō Sukeyuki, name, Itō Sukeyuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itō Sukeyuki Context triple: [Itō Sukeyuki, name, Itō Sukeyuki]
-
A.
Itō Sukeyuki
chosen
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.
-
B.
Nijō Tsuruko
Nijō Tsuruko was a Japanese noblewoman of the Nijō family and the mother of Empress Shōken, consort of Emperor Meiji.
-
C.
Yanagihara Naruko
Yanagihara Naruko was a Japanese noblewoman and concubine of Emperor Meiji, best known as the mother of Emperor Taishō.
-
D.
Yamaboko Junko
Yamaboko Junko is the grand procession of elaborately decorated festival floats that serves as the main highlight of Kyoto’s Gion Matsuri.
-
E.
Nijō Motoko
Nijō Motoko was a Japanese noblewoman of the Nijō family and the mother of Empress Teimei, consort of Emperor Taishō.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29d4aa8819093287bc71370fc05 |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f5994088190abc4b56040922c16 |
completed | March 12, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:04 p.m.