Triple
T4223014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Flint |
E94385
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Mayumi Kai
Mayumi Kai is a Japanese DJ and music producer best known as the widow of The Prodigy frontman Keith Flint.
|
E434519
|
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: Mayumi Kai | Statement: [Keith Flint, spouse, Mayumi Kai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayumi Kai Context triple: [Keith Flint, spouse, Mayumi Kai]
-
A.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
B.
Reika Kirishima
Reika Kirishima is a Japanese actress known for her role in the film adaptation of Haruki Murakami’s novel "Norwegian Wood" (2010).
-
C.
Takako Doi
Takako Doi was a pioneering Japanese politician who became the first female Speaker of the House of Representatives and a prominent leader of Japan’s socialist and opposition politics in the late 20th century.
-
D.
Naoko
Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
-
E.
Sojin Kamiyama
Sojin Kamiyama was a Japanese actor of the silent film era, best known for his prominent roles in early Hollywood productions.
- 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: Mayumi Kai Triple: [Keith Flint, spouse, Mayumi Kai]
Generated description
Mayumi Kai is a Japanese DJ and music producer best known as the widow of The Prodigy frontman Keith Flint.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mayumi Kai Target entity description: Mayumi Kai is a Japanese DJ and music producer best known as the widow of The Prodigy frontman Keith Flint.
-
A.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
B.
Reika Kirishima
Reika Kirishima is a Japanese actress known for her role in the film adaptation of Haruki Murakami’s novel "Norwegian Wood" (2010).
-
C.
Takako Doi
Takako Doi was a pioneering Japanese politician who became the first female Speaker of the House of Representatives and a prominent leader of Japan’s socialist and opposition politics in the late 20th century.
-
D.
Naoko
Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
-
E.
Sojin Kamiyama
Sojin Kamiyama was a Japanese actor of the silent film era, best known for his prominent roles in early Hollywood productions.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e0f4f18819089779c37c626762e |
completed | March 12, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e4df07a08190be5d2a516910c491 |
completed | March 14, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69b5e56c540481909ac061c6aa620a38 |
completed | March 14, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5e5c583ec8190a821f5b67e28af14 |
completed | March 14, 2026, 10:48 p.m. |
Created at: March 12, 2026, 11:04 p.m.