Triple
T23469481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kachidoki |
E569187
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Ginza area |
—
|
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: Ginza area | Statement: [Kachidoki, connectedTo, Ginza area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ginza area Context triple: [Kachidoki, connectedTo, Ginza area]
-
A.
Ginza district
The Ginza district is a famous upscale area in central Tokyo known for its luxury shopping, high-end dining, and vibrant nightlife.
-
B.
Ginza
"Ginza" is a reggaeton song by Colombian artist J Balvin that became a major Latin hit and helped solidify his international fame.
-
C.
Ginza
chosen
Ginza is a famous upscale shopping, dining, and entertainment district in central Tokyo known for its luxury boutiques, department stores, and vibrant nightlife.
-
D.
Kyobashi commercial district
The Kyobashi commercial district is a bustling business and shopping area in central Tokyo known for its mix of modern office buildings, retail stores, and dining options between Tokyo and Ginza.
-
E.
Kyōbashi commercial area
The Kyōbashi commercial area is a bustling Osaka district known for its dense concentration of shops, restaurants, and entertainment venues, as well as its major railway hub.
- 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6feb5688190ad4ce42fc9590adb |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.