Triple
T10978794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amagi |
E259442
|
entity |
| Predicate | sisterShip |
P3142
|
FINISHED |
| Object | Unryū |
E259865
|
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: Unryū | Statement: [Amagi, sisterShip, Unryū]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unryū Context triple: [Amagi, sisterShip, Unryū]
-
A.
Unryu
chosen
Unryu was a World War II-era Imperial Japanese Navy aircraft carrier that served in the Pacific Theater.
-
B.
Tsurugi
Tsurugi is a Japanese Shinkansen train service operating on the Hokuriku Shinkansen line, primarily providing all-stations shuttle connections between Toyama and Kanazawa.
-
C.
Yudachi
Yudachi was an Imperial Japanese Navy destroyer of the Shiratsuyu class that served in World War II, notably participating in several major Pacific naval engagements before being sunk in 1942.
-
D.
Banryū
Banryū was a Japanese warship that served in the late Edo period and took part in the Boshin War’s Naval Battle of Hakodate.
-
E.
Masaru
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f7b874819087bf5a858905279b |
completed | April 9, 2026, 9:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d7cb8fe08190b9de7b970968da48 |
completed | April 18, 2026, 1 a.m. |
Created at: April 8, 2026, 9:24 p.m.