Triple
T6622066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awaji Island |
E149696
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Sumoto |
E213567
|
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: Sumoto | Statement: [Awaji Island, hasCity, Sumoto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumoto Context triple: [Awaji Island, hasCity, Sumoto]
-
A.
Sumoto
chosen
Sumoto is a coastal city located on Awaji Island in Japan, known for its hot springs, scenic views of the Seto Inland Sea, and citrus production.
-
B.
Ushijima
Ushijima is a Japanese surname borne by various notable individuals, including military figures and fictional characters.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Tokushima
Tokushima is a coastal city on Japan’s Shikoku Island known for its annual Awa Odori dance festival and role as a regional cultural and economic center.
-
E.
Suzuya
Suzuya is a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af7ccaa481908b383b4fd671fa78 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89a4282ac8190aa641d466763b786 |
completed | March 29, 2026, 3:19 a.m. |
Created at: March 27, 2026, 1:58 p.m.