Triple
T12049037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 千駄ヶ谷 |
E286864
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object | 千駄ケ谷駅 |
E967155
|
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: 千駄ケ谷駅 | Statement: [千駄ヶ谷, hasRailwayStation, 千駄ケ谷駅]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 千駄ケ谷駅 Context triple: [千駄ヶ谷, hasRailwayStation, 千駄ケ谷駅]
-
A.
千駄ケ谷駅
chosen
千駄ケ谷駅は、東京都渋谷区に位置し、主にJR中央・総武線各駅停車が発着する駅です。
-
B.
Nakameguro Station
Nakameguro Station is a major railway station in Tokyo’s Meguro ward that serves as an important transit hub and gateway to the trendy Nakameguro neighborhood.
-
C.
千駄木駅
千駄木駅は、東京都文京区に位置し、東京メトロ千代田線が乗り入れる下町情緒の残るエリアの主要な地下鉄駅です。
-
D.
Musashi-Koganei Station
Musashi-Koganei Station is a railway station in Koganei, Tokyo, serving as a key stop on the JR Chūō Line for commuters and visitors in western Tokyo.
-
E.
Shinjuku-sanchome Station
Shinjuku-sanchome Station is a major underground railway station in Tokyo’s Shinjuku district that serves multiple Tokyo Metro lines and provides convenient access to shopping, entertainment, and business areas.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d904227958819084dbd5eb2566c735 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a62f0fc8190a3d15ccfb23bb788 |
completed | May 2, 2026, 2:29 p.m. |
Created at: April 8, 2026, 9:47 p.m.