Triple
T13827137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumida City |
E332279
|
entity |
| Predicate | hasJapaneseName |
P9882
|
FINISHED |
| Object | 墨田区 |
E181379
|
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: 墨田区 | Statement: [Sumida City, hasJapaneseName, 墨田区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 墨田区 Context triple: [Sumida City, hasJapaneseName, 墨田区]
-
A.
墨田区
chosen
墨田区 is a special ward in Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional shitamachi downtown atmosphere.
-
B.
世田谷区
世田谷区 is a special ward in western Tokyo known for its large residential areas, relatively high affluence, and numerous parks and cultural facilities.
-
C.
千代田区
千代田区 is a central special ward of Tokyo that serves as Japan’s political and administrative core, encompassing the Imperial Palace, the National Diet, and numerous government and corporate headquarters.
-
D.
新宿区
新宿区は、東京都心に位置し、日本有数の繁華街・オフィス街・行政機関が集まる主要な特別区です。
-
E.
文京区
文京区 is a central Tokyo ward known for its educational institutions, cultural facilities, and relatively quiet residential character.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0295d2d48190b08eba0d805bd72d |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8ea22c081909cc34f1030a8589b |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:13 p.m.