Triple
T15481881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urakami |
E376938
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Nagasaki City |
E46964
|
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: Nagasaki City | Statement: [Urakami, partOf, Nagasaki City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagasaki City Context triple: [Urakami, partOf, Nagasaki City]
-
A.
Nagasaki
chosen
Nagasaki is a major port city in southwestern Japan historically known as one of the two cities devastated by an American atomic bomb during World War II.
-
B.
Miyazaki City
Miyazaki City is a coastal city in southeastern Kyushu, Japan, known for its mild climate, beaches, and role as an administrative and cultural center of the region.
-
C.
Shimonoseki City
Shimonoseki City is a coastal city in Yamaguchi Prefecture, Japan, known as a major gateway between Honshu and Kyushu and for its historic role in maritime trade and the First Sino-Japanese War.
-
D.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
E.
Kaga City
Kaga City is a hot spring resort city in southern Ishikawa Prefecture, Japan, known for its historic onsen towns, traditional crafts, and scenic natural surroundings.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8cb4388190a3b4c92c3bb4ad4f |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff365b3980819094d3ca0b7766009c |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:34 a.m.