Triple
T10471024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wednesday |
E246920
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Miles Millar |
E443015
|
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: Miles Millar | Statement: [Wednesday, executiveProducer, Miles Millar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miles Millar Context triple: [Wednesday, executiveProducer, Miles Millar]
-
A.
Miles Millar
chosen
Miles Millar is a television writer and producer best known as the co-creator of the superhero series "Smallville."
-
B.
Tony Cox
Tony Cox is an American actor best known for his comedic roles in films such as "Bad Santa," "Me, Myself & Irene," and various parody movies.
-
C.
Mark Salling
Mark Salling was an American actor and musician best known for playing Noah "Puck" Puckerman on the television series Glee.
-
D.
John Seitz
John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
-
E.
Roy Roberts
Roy Roberts was an American character actor known for his prolific film and television career from the 1940s through the 1970s, often portraying authority figures such as businessmen, military officers, and lawmen.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b047b588190a116f4fbd4cdbc35 |
completed | April 10, 2026, 7:09 p.m. |
Created at: April 6, 2026, 12:20 p.m.