Triple
T13032005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sayonara |
E326463
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Miiko Taka
Miiko Taka was a Japanese-American actress best known for her breakthrough role opposite Marlon Brando in the 1957 film "Sayonara."
|
E1017100
|
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: Miiko Taka | Statement: [Sayonara, starring, Miiko Taka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miiko Taka Context triple: [Sayonara, starring, Miiko Taka]
-
A.
Takahito
Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
-
B.
Miki
Miki is a city in Japan located within Hyogo Prefecture, known for its traditional hardware industry and historical sites.
-
C.
Miki
Miki is a city located in Japan’s Kagawa Prefecture on the island of Shikoku.
-
D.
Mogis
Mogis is the surname of Mike Mogis, an American musician and record producer best known for his work with the indie rock band Bright Eyes and the Saddle Creek Records scene.
-
E.
Kintomo Mushakoji
Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
- 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: Miiko Taka Triple: [Sayonara, starring, Miiko Taka]
Generated description
Miiko Taka was a Japanese-American actress best known for her breakthrough role opposite Marlon Brando in the 1957 film "Sayonara."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miiko Taka Target entity description: Miiko Taka was a Japanese-American actress best known for her breakthrough role opposite Marlon Brando in the 1957 film "Sayonara."
-
A.
Takahito
Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
-
B.
Miki
Miki is a city in Japan located within Hyogo Prefecture, known for its traditional hardware industry and historical sites.
-
C.
Miki
Miki is a city located in Japan’s Kagawa Prefecture on the island of Shikoku.
-
D.
Mogis
Mogis is the surname of Mike Mogis, an American musician and record producer best known for his work with the indie rock band Bright Eyes and the Saddle Creek Records scene.
-
E.
Kintomo Mushakoji
Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efe72348190b52fb4068f5fb829 |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbcd25108190a6c4a129cde81534 |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd0d21e08190855dcbee000fc25d |
completed | May 3, 2026, 4:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce6b220c8190b1f49a9b2bfce692 |
completed | May 3, 2026, 4:26 a.m. |
Created at: April 9, 2026, 8:54 p.m.