Triple
T10017187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hida Mountains |
E199523
|
entity |
| Predicate | popularAccessPoint |
P54704
|
FINISHED |
| Object | Toyama |
E208642
|
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: Toyama | Statement: [Hida Mountains, popularAccessPoint, Toyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toyama Context triple: [Hida Mountains, popularAccessPoint, Toyama]
-
A.
Toyama
chosen
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.
-
B.
Tokorozawa
Tokorozawa is a commuter city in the Greater Tokyo area of Japan, known for its residential neighborhoods, aviation history, and role as a transport hub in southern Saitama.
-
C.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
D.
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.
-
E.
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.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd4c17848190bf1a8017e755ba75 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684c471b88190a4c79d907152b492 |
completed | May 2, 2026, 11:12 p.m. |
Created at: March 30, 2026, 8:53 p.m.