Triple
T22533347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 東京都港区 |
E557098
|
entity |
| Predicate | containsDistrict |
P22582
|
FINISHED |
| Object | 高輪 |
—
|
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: 高輪 | Statement: [東京都港区, containsDistrict, 高輪]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 高輪 Context triple: [東京都港区, containsDistrict, 高輪]
-
A.
高輪
chosen
高輪 is a district in Minato, Tokyo, known for its mix of historic temples, residential areas, and proximity to major transport hubs like Shinagawa.
-
B.
高田馬場
高田馬場 is a bustling neighborhood in Tokyo’s Shinjuku ward known for its major train station, student population, and numerous eateries and entertainment spots.
-
C.
有楽町
有楽町は、東京都千代田区に位置し、オフィス街や商業施設、劇場などが集まる繁華な都心エリアです。
-
D.
大手町
大手町 is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
-
E.
神宮前
神宮前 is a district in Shibuya, Tokyo, known for its proximity to Meiji Shrine and the fashionable Harajuku and Omotesando areas.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed88cf08190ae7e5b6bf9a80372 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.