Triple
T12650898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sone Arasuke |
E302154
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arasuke |
E302154
|
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: Arasuke | Statement: [Sone Arasuke, givenName, Arasuke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arasuke Context triple: [Sone Arasuke, givenName, Arasuke]
-
A.
Sone Arasuke
chosen
Sone Arasuke was a Japanese statesman and diplomat who played a key role in Japan’s imperial expansion in East Asia during the late Meiji period.
-
B.
Asakura
Asakura is a city in Fukuoka Prefecture, Japan, known for its rural landscapes, historic sites, and agricultural products such as fruits and vegetables.
-
C.
Takamori
Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
-
D.
Kazuno
Kazuno is a city in northern Japan known for its hot springs, traditional festivals, and mountainous rural scenery.
-
E.
Akiro
Akiro is a wise and skilled wizard who serves as one of Conan the Barbarian’s key companions in the film "Conan the Destroyer."
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9615f28cc81908e37249d7ab5ed74 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c730b5c8190ae8dbb476e53729e |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:18 p.m.