Triple
T1310763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Prefecture |
E27983
|
entity |
| Predicate | hasMajorBusinessDistrict |
P459
|
FINISHED |
| Object | Ginza |
E71727
|
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: Ginza | Statement: [Tokyo Prefecture, hasMajorBusinessDistrict, Ginza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ginza Context triple: [Tokyo Prefecture, hasMajorBusinessDistrict, Ginza]
-
A.
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.
-
B.
Otemachi
Otemachi is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
-
C.
Toranomon
Toranomon is a central business district in Tokyo known for its government offices, corporate headquarters, and proximity to major transport and commercial hubs.
-
D.
Akasaka
Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
-
E.
Nihonbashi
Nihonbashi is a historic commercial district in central Tokyo known for its iconic bridge, traditional merchants, and major financial and retail centers.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c1560f888190bdd9107b08395e0b |
completed | March 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1731ebe481908ffd1a670ae86286 |
completed | March 9, 2026, 6:53 p.m. |
Created at: March 1, 2026, 7:51 p.m.