Triple
T14249222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 赤坂御用地 |
E353212
|
entity |
| Predicate | 周辺地域 |
P17964
|
FINISHED |
| Object |
青山
青山は、東京都港区と渋谷区にまたがる洗練された商業エリアで、高級ブティックやカフェ、ギャラリーが集まるおしゃれな街として知られています。
|
E1090343
|
NE FINISHED |
How this triple was built (4 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: 青山 | Statement: [赤坂御用地, 周辺地域, 青山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 青山 Context triple: [赤坂御用地, 周辺地域, 青山]
-
A.
Wuling Mountain
Wuling Mountain is a prominent peak in northern China known as the highest summit of the Yan Mountains range.
-
B.
Mianshan Mountain
Mianshan Mountain is a scenic and historically significant mountain in Shanxi Province, China, known for its dramatic cliffs, temples, and cultural heritage sites.
-
C.
Tianshou Mountain
Tianshou Mountain is a notable mountain in China, recognized for its scenic landscapes and cultural significance.
-
D.
Xiaoguanyin Mountain
Xiaoguanyin Mountain is a prominent volcanic peak within Taiwan’s Yangmingshan range, known for its rugged terrain and scenic hiking routes.
-
E.
Wushan Mountains
The Wushan Mountains are a prominent mountain range in southwestern China, best known for their dramatic gorges along the Yangtze River and their role as a natural boundary around the Sichuan region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 青山 Triple: [赤坂御用地, 周辺地域, 青山]
Generated description
青山は、東京都港区と渋谷区にまたがる洗練された商業エリアで、高級ブティックやカフェ、ギャラリーが集まるおしゃれな街として知られています。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 青山 Target entity description: 青山は、東京都港区と渋谷区にまたがる洗練された商業エリアで、高級ブティックやカフェ、ギャラリーが集まるおしゃれな街として知られています。
-
A.
Wuling Mountain
Wuling Mountain is a prominent peak in northern China known as the highest summit of the Yan Mountains range.
-
B.
Mianshan Mountain
Mianshan Mountain is a scenic and historically significant mountain in Shanxi Province, China, known for its dramatic cliffs, temples, and cultural heritage sites.
-
C.
Tianshou Mountain
Tianshou Mountain is a notable mountain in China, recognized for its scenic landscapes and cultural significance.
-
D.
Xiaoguanyin Mountain
Xiaoguanyin Mountain is a prominent volcanic peak within Taiwan’s Yangmingshan range, known for its rugged terrain and scenic hiking routes.
-
E.
Wushan Mountains
The Wushan Mountains are a prominent mountain range in southwestern China, best known for their dramatic gorges along the Yangtze River and their role as a natural boundary around the Sichuan region.
- F. None of above. chosen
Provenance (5 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6295ef9081909cfb0c1283bca21a |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd325815d48190b070866f41986847 |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd367fd9788190bd25f057d1f0942c |
completed | May 8, 2026, 1:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd37c1f4c0819085f5c577e673e9df |
completed | May 8, 2026, 1:09 a.m. |
Created at: April 10, 2026, 1:08 a.m.