Triple
T18676357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namba City |
E456611
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Namba district |
—
|
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: Namba district | Statement: [Namba City, district, Namba district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namba district Context triple: [Namba City, district, Namba district]
-
A.
Namba district
chosen
Namba district is a major entertainment and shopping area in Osaka, Japan, known for its neon lights, bustling nightlife, and iconic landmarks.
-
B.
Kanda district
Kanda district is a historic commercial and cultural area in central Tokyo known for its old bookstores, electronics shops, and traditional shrines.
-
C.
Tsurumai district
Tsurumai district is an urban neighborhood in Nagoya, Japan, known for its central park, cultural facilities, and convenient access to public transportation.
-
D.
Senkawa district
Senkawa district is a residential neighborhood in Tokyo, Japan, known for its convenient urban location and access to public transportation.
-
E.
Yoichi District
Yoichi District is a rural administrative district in western Hokkaido, Japan, known for its coastal towns, fruit orchards, and whisky production.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b5a52c81908a71ac86544fb6aa |
completed | April 19, 2026, 10:27 p.m. |
Created at: April 10, 2026, 11:48 a.m.