Triple
T7715130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 和光市 |
E174860
|
entity |
| Predicate | hasJapaneseName |
P9882
|
FINISHED |
| Object | 和光市 |
E174860
|
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: 和光市 | Statement: [和光市, hasJapaneseName, 和光市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 和光市 Context triple: [和光市, hasJapaneseName, 和光市]
-
A.
和光市
chosen
和光市 is a suburban city in southern Saitama Prefecture, Japan, known for hosting research institutes and serving as a residential area for commuters to Tokyo.
-
B.
柏原市
柏原市は、大阪府南東部に位置し、歴史ある寺社やぶどう栽培などで知られる中規模の都市です。
-
C.
川越市
川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
-
D.
丹波市
丹波市 is a rural city in central Hyōgo Prefecture, Japan, known for its historic castle town atmosphere, agricultural products, and scenic natural landscapes.
-
E.
宍粟市
宍粟市は、兵庫県西部の中国山地に位置し、豊かな森林資源と自然環境を特徴とする市です。
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702cbe74081908502ac670515fa3c |
completed | March 27, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b508fa2081908ed05ca8c4815249 |
completed | March 29, 2026, 5:13 a.m. |
Created at: March 27, 2026, 4:04 p.m.