Triple
T21160529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel LaRusso |
E521428
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Mr. Miyagi |
—
|
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: Mr. Miyagi | Statement: [Daniel LaRusso, closeFriend, Mr. Miyagi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Miyagi Context triple: [Daniel LaRusso, closeFriend, Mr. Miyagi]
-
A.
Mr. Miyagi
chosen
Mr. Miyagi is the wise, soft-spoken karate master and mentor from "The Karate Kid" film series, known for teaching life lessons through unconventional training methods.
-
B.
John Kreese
John Kreese is the ruthless sensei of the Cobra Kai dojo in the Karate Kid franchise, known for his "no mercy" philosophy and antagonistic role against Daniel LaRusso and Mr. Miyagi.
-
C.
Sensei Wu
Sensei Wu is a wise, elderly ninja master from the Lego Ninjago franchise who mentors the main ninja heroes in their battles against evil.
-
D.
Kenichi Hagiwara
Kenichi Hagiwara was a prominent Japanese actor and singer known for his charismatic performances in film, television, and music from the 1970s onward.
-
E.
Daisuke Ryū
Daisuke Ryū is a Japanese actor best known for his roles in Akira Kurosawa’s historical epics and other period films.
- 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7252f70888190b8e6109cc4099ecc |
completed | April 21, 2026, 7:20 a.m. |
Created at: April 16, 2026, 2:59 p.m.