Triple
T11867401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uesugi Kenshin |
E282320
|
entity |
| Predicate | honorificName |
P6819
|
FINISHED |
| Object | Kenshin |
E282320
|
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: Kenshin | Statement: [Uesugi Kenshin, honorificName, Kenshin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenshin Context triple: [Uesugi Kenshin, honorificName, Kenshin]
-
A.
Uesugi Kenshin
chosen
Uesugi Kenshin was a prominent Sengoku-period Japanese daimyō famed for his military prowess, strategic genius, and rivalry with Takeda Shingen.
-
B.
Kodama Kenji
Kodama Kenji is a Japanese anime director best known for his work on series such as City Hunter and Detective Conan.
-
C.
Kinsaku
Kinsaku is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and literary figure.
-
D.
Kodama Gentarō
Kodama Gentarō was a Japanese general and statesman who served as Governor-General of Taiwan, playing a key role in establishing Japanese colonial administration there in the late 19th and early 20th centuries.
-
E.
Kaoru
Kaoru is a central character in the later chapters of the classic Japanese novel "The Tale of Genji," known for his gentle nature and complex romantic entanglements.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73a233081909449ab294d01a512 |
completed | April 10, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f2819229ec81908a3bc5579d661c20 |
completed | April 29, 2026, 10:09 p.m. |
Created at: April 8, 2026, 9:43 p.m.