Triple
T3877527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satō |
E92538
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Naoko Satō
Naoko Satō is a Japanese given name borne by various notable individuals, including figures in entertainment, sports, and the arts.
|
E398912
|
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: Naoko Satō | Statement: [Satō, hasNotableBearer, Naoko Satō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naoko Satō Context triple: [Satō, hasNotableBearer, Naoko Satō]
-
A.
Naoko Takeshita
Naoko Takeshita was the wife of former Japanese Prime Minister Noboru Takeshita and a member of a prominent political family in Japan.
-
B.
Hiroko Satō
Hiroko Satō was the wife of Eisaku Satō, the Japanese prime minister and Nobel Peace Prize laureate.
-
C.
Akiko Takeshita
Akiko Takeshita is a Japanese actress known internationally for her supporting role in the film "Lost in Translation."
-
D.
Shinobu Hashimoto
Shinobu Hashimoto was a renowned Japanese screenwriter best known for his collaborations with Akira Kurosawa on classic films such as Rashomon, Seven Samurai, and Ikiru.
-
E.
Makiko Tanaka
Makiko Tanaka is a Japanese politician and former foreign minister, known as the outspoken daughter of influential former Prime Minister Kakuei Tanaka.
- 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: Naoko Satō Triple: [Satō, hasNotableBearer, Naoko Satō]
Generated description
Naoko Satō is a Japanese given name borne by various notable individuals, including figures in entertainment, sports, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naoko Satō Target entity description: Naoko Satō is a Japanese given name borne by various notable individuals, including figures in entertainment, sports, and the arts.
-
A.
Naoko Takeshita
Naoko Takeshita was the wife of former Japanese Prime Minister Noboru Takeshita and a member of a prominent political family in Japan.
-
B.
Hiroko Satō
Hiroko Satō was the wife of Eisaku Satō, the Japanese prime minister and Nobel Peace Prize laureate.
-
C.
Akiko Takeshita
Akiko Takeshita is a Japanese actress known internationally for her supporting role in the film "Lost in Translation."
-
D.
Shinobu Hashimoto
Shinobu Hashimoto was a renowned Japanese screenwriter best known for his collaborations with Akira Kurosawa on classic films such as Rashomon, Seven Samurai, and Ikiru.
-
E.
Makiko Tanaka
Makiko Tanaka is a Japanese politician and former foreign minister, known as the outspoken daughter of influential former Prime Minister Kakuei Tanaka.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec72fa7c81909c73b3cf90597e9a |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b52845684c8190b6f0676319a6fc3c |
completed | March 14, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_69b5290462a88190892c0bcc3a74f2fa |
completed | March 14, 2026, 9:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b529600884819098cb208e38e6281a |
completed | March 14, 2026, 9:24 a.m. |
Created at: March 9, 2026, 3:20 p.m.