Triple
T19689047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 御堂筋 |
E472785
|
entity |
| Predicate | parallelTo |
P1868
|
FINISHED |
| Object | 堺筋 |
—
|
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: 堺筋 | Statement: [御堂筋, parallelTo, 堺筋]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 堺筋 Context triple: [御堂筋, parallelTo, 堺筋]
-
A.
堺筋
chosen
堺筋 is a major north–south arterial street in central Osaka, Japan, known for its dense mix of commercial districts, electronics shops, and historic neighborhoods.
-
B.
Tenjinbashi-suji street
Tenjinbashi-suji street is a famous and historically significant shopping arcade in Osaka, Japan, known as one of the longest covered shopping streets in the country.
-
C.
Motomachi
Motomachi is a stylish shopping and entertainment district in Yokohama known for its fashionable boutiques, cafes, and Western-influenced atmosphere.
-
D.
Motomachi
Motomachi is a central commercial and entertainment district in Osaka known for its bustling shopping streets and proximity to major transport hubs.
-
E.
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.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6420e5b788190a63ff6b83383b0e8 |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:45 p.m.