Triple
T23216917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 神戸市 |
E580770
|
entity |
| Predicate | hasWard |
P14475
|
FINISHED |
| Object | 垂水区 |
—
|
NE NERFINISHED |
How this triple was built (3 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: 垂水区 | Statement: [神戸市, hasWard, 垂水区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 垂水区 Context triple: [神戸市, hasWard, 垂水区]
-
A.
Huanggoushu Waterfall region
The Huanggoushu Waterfall region is a famous scenic area in Guizhou, China, centered around one of Asia’s largest waterfalls and known for its dramatic karst landscapes and lush natural beauty.
-
B.
Baishizhou area
Baishizhou area is a densely populated urban neighborhood in Shenzhen, China, known for its large urban village, vibrant street life, and proximity to major commercial and tech districts.
-
C.
Kizu River area
The Kizu River area is a scenic riverine landscape in Japan known for its natural beauty, historical sites, and recreational opportunities along the Kizu River.
-
D.
Mukogawa floodplain
Mukogawa floodplain is the low-lying, periodically inundated landform along the Mukogawa River in Japan, known for its riverine ecosystems and role in natural flood management.
-
E.
Chishui River region
The Chishui River region is a scenic and ecologically significant area in northern Guizhou, China, known for its river valleys, biodiversity, and role in the historic Long March.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 垂水区 Target entity description: 垂水区は、兵庫県南部の神戸市に位置し、明石海峡大橋や海沿いの景観で知られる住宅・商業エリアです。
-
A.
Huanggoushu Waterfall region
The Huanggoushu Waterfall region is a famous scenic area in Guizhou, China, centered around one of Asia’s largest waterfalls and known for its dramatic karst landscapes and lush natural beauty.
-
B.
Baishizhou area
Baishizhou area is a densely populated urban neighborhood in Shenzhen, China, known for its large urban village, vibrant street life, and proximity to major commercial and tech districts.
-
C.
Kizu River area
The Kizu River area is a scenic riverine landscape in Japan known for its natural beauty, historical sites, and recreational opportunities along the Kizu River.
-
D.
Mukogawa floodplain
Mukogawa floodplain is the low-lying, periodically inundated landform along the Mukogawa River in Japan, known for its riverine ecosystems and role in natural flood management.
-
E.
Chishui River region
The Chishui River region is a scenic and ecologically significant area in northern Guizhou, China, known for its river valleys, biodiversity, and role in the historic Long March.
- F. None of above. chosen
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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f19165949c81908e4d66a8a2b0a25a |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.