Triple
T5430788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kissy Suzuki |
E121483
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Mie Hama
Mie Hama is a Japanese actress best known internationally for her role as a Bond girl in the James Bond film "You Only Live Twice."
|
E519621
|
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: Mie Hama | Statement: [Kissy Suzuki, portrayedBy, Mie Hama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mie Hama Context triple: [Kissy Suzuki, portrayedBy, Mie Hama]
-
A.
Maki Horikita
Maki Horikita is a Japanese actress known for her leading roles in popular television dramas and films during the 2000s and early 2010s.
-
B.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
C.
Reika Kirishima
Reika Kirishima is a Japanese actress known for her role in the film adaptation of Haruki Murakami’s novel "Norwegian Wood" (2010).
-
D.
Esaki Reona
Esaki Reona, better known internationally as Leo Esaki, is a Japanese physicist and Nobel laureate renowned for his pioneering work on quantum tunneling and the invention of the Esaki (tunnel) diode.
-
E.
Chiaki Mukai
Chiaki Mukai is a Japanese physician and astronaut who became the first Japanese woman to fly in space and a veteran of two NASA Space Shuttle missions.
- 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: Mie Hama Triple: [Kissy Suzuki, portrayedBy, Mie Hama]
Generated description
Mie Hama is a Japanese actress best known internationally for her role as a Bond girl in the James Bond film "You Only Live Twice."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mie Hama Target entity description: Mie Hama is a Japanese actress best known internationally for her role as a Bond girl in the James Bond film "You Only Live Twice."
-
A.
Maki Horikita
Maki Horikita is a Japanese actress known for her leading roles in popular television dramas and films during the 2000s and early 2010s.
-
B.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
C.
Reika Kirishima
Reika Kirishima is a Japanese actress known for her role in the film adaptation of Haruki Murakami’s novel "Norwegian Wood" (2010).
-
D.
Esaki Reona
Esaki Reona, better known internationally as Leo Esaki, is a Japanese physicist and Nobel laureate renowned for his pioneering work on quantum tunneling and the invention of the Esaki (tunnel) diode.
-
E.
Chiaki Mukai
Chiaki Mukai is a Japanese physician and astronaut who became the first Japanese woman to fly in space and a veteran of two NASA Space Shuttle missions.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd883e5e10819091e159dfd245e94d |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac6285081909afa6e91a023f6d5 |
completed | March 22, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69bf3c43ffe88190b8d2a10ea8a9a455 |
completed | March 22, 2026, 12:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf3ce7d6388190a9cd22f76f4420e0 |
completed | March 22, 2026, 12:50 a.m. |
Created at: March 20, 2026, 2:06 p.m.