Triple
T235082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namba |
E4490
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Shinsaibashi |
E19641
|
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: Shinsaibashi | Statement: [Namba, near, Shinsaibashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shinsaibashi Context triple: [Namba, near, Shinsaibashi]
-
A.
Shinsaibashi
chosen
Shinsaibashi is a major shopping and entertainment district in central Osaka, Japan, known for its covered arcade, fashion boutiques, and vibrant nightlife.
-
B.
Motomachi
Motomachi is a historic commercial and shopping district in Kobe, Japan, known for its fashionable boutiques, cafes, and proximity to the city’s Chinatown and waterfront.
-
C.
Omotesando
Omotesando is a fashionable, tree-lined avenue in central Tokyo known for its high-end boutiques, modern architecture, and trendy cafes.
-
D.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
E.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25cc9ab2c81909af278a07f86aa1e |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4d03b948c8190b9b6f8e86c3249e8 |
completed | March 1, 2026, 11:48 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.