Triple
T21160530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel LaRusso |
E521428
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Ali Mills |
—
|
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: Ali Mills | Statement: [Daniel LaRusso, closeFriend, Ali Mills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ali Mills Context triple: [Daniel LaRusso, closeFriend, Ali Mills]
-
A.
Ali Mills
chosen
Ali Mills is a central teenage character in the original "The Karate Kid" film, known as Daniel LaRusso’s love interest and a key figure in the rivalry between him and Johnny Lawrence.
-
B.
Kim Mills
Kim Mills is the teenage daughter of ex-CIA operative Bryan Mills in the "Taken" film series, whose kidnapping sets off the franchise’s central rescue-driven action.
-
C.
Ian Miller
Ian Miller is the non-Greek schoolteacher who marries Toula Portokalos and navigates her exuberant Greek-American family in the romantic comedy film "My Big Fat Greek Wedding."
-
D.
Eli Mills
Eli Mills is a primary antagonist in the Jurassic World film series, known as a manipulative businessman who exploits dinosaurs for profit.
-
E.
Lash Miller
Lash Miller was a prominent Canadian chemist and professor at the University of Toronto, known for his influential work in physical chemistry and chemical education.
- 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.