Triple
T13843909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hirano |
E332740
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Miki Hirano
Miki Hirano is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Hirano.
|
E1083475
|
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: Miki Hirano | Statement: [Hirano, hasNotableBearer, Miki Hirano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miki Hirano Context triple: [Hirano, hasNotableBearer, Miki Hirano]
-
A.
Miki Satō
Miki Satō is a Japanese singer-songwriter known for her emotionally expressive vocals and contributions to anime theme songs.
-
B.
Eriko Miyagawa
Eriko Miyagawa is a television producer best known for her executive production work on the series "Shōgun."
-
C.
Miki Sudo
Miki Sudo is an American competitive eater best known as a multi-time women's champion in professional hot dog eating contests.
-
D.
Kiko Mizuhara
Kiko Mizuhara is a Japanese-American model, actress, and designer known for her prominent work in fashion and film, as well as her influence in contemporary Japanese pop culture.
-
E.
Reki Kawahara
Reki Kawahara is a Japanese light novel author best known for writing the popular series Sword Art Online and Accel World, both of which have received successful anime adaptations.
- 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: Miki Hirano Triple: [Hirano, hasNotableBearer, Miki Hirano]
Generated description
Miki Hirano is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Hirano.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miki Hirano Target entity description: Miki Hirano is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Hirano.
-
A.
Miki Satō
Miki Satō is a Japanese singer-songwriter known for her emotionally expressive vocals and contributions to anime theme songs.
-
B.
Eriko Miyagawa
Eriko Miyagawa is a television producer best known for her executive production work on the series "Shōgun."
-
C.
Miki Sudo
Miki Sudo is an American competitive eater best known as a multi-time women's champion in professional hot dog eating contests.
-
D.
Kiko Mizuhara
Kiko Mizuhara is a Japanese-American model, actress, and designer known for her prominent work in fashion and film, as well as her influence in contemporary Japanese pop culture.
-
E.
Reki Kawahara
Reki Kawahara is a Japanese light novel author best known for writing the popular series Sword Art Online and Accel World, both of which have received successful anime adaptations.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02afce788190a74dce4e6a3569fa |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7d20f548190a9f48e8c613abed4 |
completed | May 7, 2026, 8:36 p.m. |
| NEDg | Description generation | batch_69fd0450cd888190a023490e459231eb |
completed | May 7, 2026, 9:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd04b618d88190bcd95947867b4775 |
completed | May 7, 2026, 9:31 p.m. |
Created at: April 9, 2026, 10:13 p.m.