Triple
T13572100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gotō Shinpei |
E324188
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Shinpei |
E289656
|
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: Shinpei | Statement: [Gotō Shinpei, givenName, Shinpei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shinpei Context triple: [Gotō Shinpei, givenName, Shinpei]
-
A.
Shinpei
chosen
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
-
B.
Kenjirō
Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
-
C.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
-
D.
Shigeo
Shigeo is a Japanese given name commonly used for males.
-
E.
Kinnosuke
Kinnosuke is the given name of the renowned Japanese novelist Natsume Sōseki, a central figure in modern Japanese literature.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0106cb48190b20eb9bda131a68a |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64e47f1c8190a4ad09bc96d35b69 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 9, 2026, 9:48 p.m.