Triple
T20666523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takahito, Prince Mikasa |
E507901
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Yuriko, Princess Mikasa |
—
|
NE NERFINISHED |
How this triple was built (2 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: Yuriko, Princess Mikasa | Statement: [Takahito, Prince Mikasa, spouse, Yuriko, Princess Mikasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuriko, Princess Mikasa Context triple: [Takahito, Prince Mikasa, spouse, Yuriko, Princess Mikasa]
-
A.
Yuriko
chosen
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
-
B.
Mikasa
Mikasa is a small city in Hokkaido, Japan, known for its coal mining history and rich fossil discoveries.
-
C.
Mikasa
Mikasa is a Japanese imperial family name most prominently associated with Prince Mikasa and his descendants within the modern Japanese monarchy.
-
D.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
E.
Mai Shiranui
Mai Shiranui is a popular and iconic kunoichi (female ninja) character from SNK’s fighting games, known for her revealing outfit, agile fighting style, and fiery fan-based attacks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c39dd48190965d65537592aef6 |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.