Triple
T15278582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginza Six |
E365206
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Chuo-ku |
E849314
|
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: Chuo-ku | Statement: [Ginza Six, locatedIn, Chuo-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chuo-ku Context triple: [Ginza Six, locatedIn, Chuo-ku]
-
A.
Chuo Ward
Chuo Ward is a central administrative district of Kumamoto City in Japan, known for its role as a key commercial and civic hub of the area.
-
B.
Chuo Ward
chosen
Chuo Ward is a central special ward of Tokyo, Japan, known for its major commercial districts like Ginza and Nihonbashi and its role as a key business and shopping hub.
-
C.
Higashi-ku
Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
-
D.
Seo District
Seo District is a western coastal district of Incheon, South Korea, known for its industrial complexes, port facilities, and growing residential areas.
-
E.
Bunkyō-ku
Bunkyō-ku is a central Tokyo ward known for its universities, cultural institutions, and quiet residential neighborhoods.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00953bc848190b83919f39d5ee37b |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00baf8a2648190adf3ad3af118187f |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 3:14 a.m.