Triple
T20104255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 墨田区 |
E181379
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | 東京ソラマチ |
—
|
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: 東京ソラマチ | Statement: [墨田区, hasLandmark, 東京ソラマチ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 東京ソラマチ Context triple: [墨田区, hasLandmark, 東京ソラマチ]
-
A.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
B.
Hayashi Department Store
Hayashi Department Store is a historic Japanese-era department store in Tainan, Taiwan, renowned for its preserved architecture and role as a cultural and commercial landmark.
-
C.
Matsuya Ginza department store
Matsuya Ginza department store is a historic, upscale Japanese department store in Tokyo’s Ginza district, known for its fashion, luxury goods, and distinctive modern façade.
-
D.
Odakyu department store
Odakyu department store is a major Japanese department store chain best known for its large flagship store complex in Tokyo’s Shinjuku district.
-
E.
Tokyo Solamachi
chosen
Tokyo Solamachi is a large shopping, dining, and entertainment complex located at the base of Tokyo Skytree in Tokyo, Japan.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666daf73c819089f02ca6faa2c283 |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:27 p.m.