Triple
T12030550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dash Mihok |
E286393
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dash Mihok |
E286393
|
NE FINISHED |
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: Dash Mihok | Statement: [Dash Mihok, name, Dash Mihok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dash Mihok Context triple: [Dash Mihok, name, Dash Mihok]
-
A.
Dash Mihok
chosen
Dash Mihok is an American actor best known for his roles in films like "The Thin Red Line" and the TV series "Ray Donovan."
-
B.
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.
-
C.
Mikami
Mikami is a Japanese surname most notably associated with Shinji Mikami, the influential video game director and creator of the Resident Evil series.
-
D.
Makkari
Makkari is a super-speed-powered Eternal and one of the central immortal heroes featured in the Marvel Cinematic Universe film "Eternals."
-
E.
Komae
Komae is a small residential city in Tokyo Metropolis, Japan, known for its suburban character and proximity to central Tokyo.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903f24490819092ec911d6ed8e24b |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d4f4c80819082ffc0c5aa3505a0 |
completed | May 1, 2026, 12:32 p.m. |
Created at: April 8, 2026, 9:47 p.m.