Triple
T1770394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sukki |
E38860
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Nagano |
E80334
|
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: Nagano | Statement: [Sukki, location, Nagano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagano Context triple: [Sukki, location, Nagano]
-
A.
Nagano
Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
-
B.
Niigata
Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
-
C.
Nagano Prefecture
chosen
Nagano Prefecture is a mountainous region in central Japan renowned for its ski resorts, natural scenery, and role as the venue of the 1998 Winter Olympics.
-
D.
Toyama
Toyama is a coastal city in central Japan known as the capital of Toyama Prefecture, serving as a regional industrial and transportation hub on the Sea of Japan.
-
E.
Oita
Ōita is a coastal city on Japan’s Kyushu island known for its hot springs, regional cuisine, and role as the capital of Ōita Prefecture.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648eb9488190b1be2d2b6d259634 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdb8d89e248190a9cd92e9f61697f8 |
completed | March 20, 2026, 9:15 p.m. |
Created at: March 4, 2026, 7:31 p.m.