Triple
T18159233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sannomiya Station |
E434711
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Kobe Chinatown Nankinmachi |
—
|
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: Kobe Chinatown Nankinmachi | Statement: [Sannomiya Station, near, Kobe Chinatown Nankinmachi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobe Chinatown Nankinmachi Context triple: [Sannomiya Station, near, Kobe Chinatown Nankinmachi]
-
A.
Kobe Chinatown
Kobe Chinatown is a compact, bustling Chinese district in central Kobe, Japan, known for its vibrant streets, food stalls, and cultural festivals.
-
B.
Yokohama Chinatown
Yokohama Chinatown is one of Japan’s largest and most famous Chinese districts, known for its vibrant streets, temples, and numerous Chinese restaurants and shops.
-
C.
Kobe Nankinmachi
chosen
Kobe Nankinmachi is a famous Chinatown district in Kobe, Japan, known for its Chinese restaurants, shops, and vibrant cultural festivals.
-
D.
China Town
"China Town" is a 1962 Hindi-language Indian crime thriller film starring Shammi Kapoor in a double role, known for its blend of suspense, music, and drama.
-
E.
China Town
China Town was the original name of the Nevada settlement that later became the town of Dayton.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec0e0388190af11ac167411da96 |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 10:30 a.m.