Triple
T14900029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taishi |
E359979
|
entity |
| Predicate | hasJapaneseName |
P9882
|
FINISHED |
| Object |
太子町
太子町は、聖徳太子ゆかりの史跡や寺院が点在することで知られる日本の町です。
|
E1124774
|
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: 太子町 | Statement: [Taishi, hasJapaneseName, 太子町]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 太子町 Context triple: [Taishi, hasJapaneseName, 太子町]
-
A.
瑞穂町
瑞穂町は、日本の東京都西多摩郡に位置する住宅地と自然が混在する町です。
-
B.
Takahata Town
Takahata Town is a rural municipality in northeastern Japan known for its agricultural production, hot springs, and historical sites.
-
C.
Matsushima Town
Matsushima Town is a coastal municipality in northeastern Japan famed for its scenic bay dotted with pine-covered islets, traditionally celebrated as one of Japan’s Three Most Beautiful Views.
-
D.
Toyako Town
Toyako Town is a lakeside town in Hokkaido, Japan, known for its scenic volcanic landscapes, hot springs, and outdoor recreation around Lake Tōya.
-
E.
Takeda town
Takeda town is a small Japanese settlement in Hyōgo Prefecture known for its scenic valley setting beneath the historic Takeda Castle Ruins, often called the “Castle in the Sky.”
- 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: 太子町 Triple: [Taishi, hasJapaneseName, 太子町]
Generated description
太子町は、聖徳太子ゆかりの史跡や寺院が点在することで知られる日本の町です。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 太子町 Target entity description: 太子町は、聖徳太子ゆかりの史跡や寺院が点在することで知られる日本の町です。
-
A.
瑞穂町
瑞穂町は、日本の東京都西多摩郡に位置する住宅地と自然が混在する町です。
-
B.
Takahata Town
Takahata Town is a rural municipality in northeastern Japan known for its agricultural production, hot springs, and historical sites.
-
C.
Matsushima Town
Matsushima Town is a coastal municipality in northeastern Japan famed for its scenic bay dotted with pine-covered islets, traditionally celebrated as one of Japan’s Three Most Beautiful Views.
-
D.
Toyako Town
Toyako Town is a lakeside town in Hokkaido, Japan, known for its scenic volcanic landscapes, hot springs, and outdoor recreation around Lake Tōya.
-
E.
Takeda town
Takeda town is a small Japanese settlement in Hyōgo Prefecture known for its scenic valley setting beneath the historic Takeda Castle Ruins, often called the “Castle in the Sky.”
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded609bf68819099ca3aa3fe1acadc |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b6a8aac8190ad062b80d384fb14 |
completed | May 8, 2026, 11:02 p.m. |
| NEDg | Description generation | batch_69fe6c68c46881909e7c748c0dff73d5 |
completed | May 8, 2026, 11:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6d1eea60819087ca2ebc7d0a8994 |
completed | May 8, 2026, 11:09 p.m. |
Created at: April 10, 2026, 2:11 a.m.