Triple
T4605336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 小和田雅子 |
E100417
|
entity |
| Predicate | 父親 |
P1908
|
FINISHED |
| Object |
小和田恒
小和田恒は、日本の外交官として国連大使や国際司法裁判所判事を務めたほか、皇后雅子の父としても知られる人物である。
|
E456041
|
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: 小和田恒 | Statement: [小和田雅子, 父親, 小和田恒]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 小和田恒 Context triple: [小和田雅子, 父親, 小和田恒]
-
A.
小和田雅子
小和田雅子は、日本の皇太子妃を経て現在の皇后であり、外交官出身の高い教養と国際感覚を持つ人物です。
-
B.
井深大
井深大は、ソニー株式会社の共同創業者として知られる日本の実業家・技術者です。
-
C.
西村祥治
西村祥治 was an Imperial Japanese Navy admiral during World War II who commanded major surface forces in the Pacific War.
-
D.
天野 浩
天野 浩は、青色発光ダイオード(青色LED)の発明で2014年にノーベル物理学賞を受賞した日本の物理学者・工学者です。
-
E.
久米邦武
久米邦武 was a Meiji-era Japanese historian and scholar best known for documenting the Iwakura Mission and advancing modern historical studies in Japan.
- 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: 小和田恒 Triple: [小和田雅子, 父親, 小和田恒]
Generated description
小和田恒は、日本の外交官として国連大使や国際司法裁判所判事を務めたほか、皇后雅子の父としても知られる人物である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 小和田恒 Target entity description: 小和田恒は、日本の外交官として国連大使や国際司法裁判所判事を務めたほか、皇后雅子の父としても知られる人物である。
-
A.
小和田雅子
小和田雅子は、日本の皇太子妃を経て現在の皇后であり、外交官出身の高い教養と国際感覚を持つ人物です。
-
B.
井深大
井深大は、ソニー株式会社の共同創業者として知られる日本の実業家・技術者です。
-
C.
西村祥治
西村祥治 was an Imperial Japanese Navy admiral during World War II who commanded major surface forces in the Pacific War.
-
D.
天野 浩
天野 浩は、青色発光ダイオード(青色LED)の発明で2014年にノーベル物理学賞を受賞した日本の物理学者・工学者です。
-
E.
久米邦武
久米邦武 was a Meiji-era Japanese historian and scholar best known for documenting the Iwakura Mission and advancing modern historical studies in Japan.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599b1f0881909fd693b81ff44f98 |
completed | March 20, 2026, 2:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfa6d24808190a4edc426b8b719cd |
completed | March 21, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_69bdfbea628c81908f96e706d650ef9f |
completed | March 21, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdfc97fc54819093e0cff18a40bde2 |
completed | March 21, 2026, 2:04 a.m. |
Created at: March 20, 2026, 1:12 p.m.