Triple
T19689027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 御堂筋 |
E472785
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | 大阪府 |
—
|
NE NERFINISHED |
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: 大阪府 | Statement: [御堂筋, locatedIn, 大阪府]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 大阪府 Context triple: [御堂筋, locatedIn, 大阪府]
-
A.
Osaka Prefecture
chosen
Osaka Prefecture is a populous and economically vital region in Japan’s Kansai area, centered on the city of Osaka and known as a major hub of commerce, industry, and culture.
-
B.
Wakayama Prefecture
Wakayama Prefecture is a coastal region in Japan’s Kansai area known for its sacred sites on the Kii Peninsula, including Mount Koya and the Kumano Kodo pilgrimage routes.
-
C.
兵庫県
兵庫県は近畿地方に位置し、日本海から瀬戸内海、日本海側の山岳地帯や都市部の神戸・姫路など多様な地形と産業を持つ日本の県である。
-
D.
Kyoto Prefecture
Kyoto Prefecture is a region in Japan’s Kansai area known for its historic capital city of Kyoto, famous temples, traditional culture, and well-preserved heritage sites.
-
E.
Nara Prefecture
Nara Prefecture is a landlocked region in Japan’s Kansai area known for its ancient temples, historic capital city of Nara, and free-roaming deer in Nara Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6420e5b788190a63ff6b83383b0e8 |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:45 p.m.