Triple
T6994573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Coates |
E162176
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kim Coates |
E162176
|
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: Kim Coates | Statement: [Kim Coates, name, Kim Coates]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Coates Context triple: [Kim Coates, name, Kim Coates]
-
A.
Kim Coates
chosen
Kim Coates is a Canadian-American actor best known for his role as the ruthless yet charismatic biker Tig Trager on the television series "Sons of Anarchy."
-
B.
Jim Coates
Jim Coates is the husband of Katie Coates, known primarily in relation to her.
-
C.
William Paul Coates
William Paul Coates is an American publisher, activist, and founder of Black Classic Press, known for preserving and promoting works of African and African-American literature.
-
D.
Jon Cooksey
Jon Cooksey is a television and film writer best known for co-writing the popular Disney Channel movie "Halloweentown."
-
E.
Charlie Shotwell
Charlie Shotwell is an American child actor known for roles in films such as "Captain Fantastic," "The Glass Castle," and "Troop Zero."
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbeaa88c8190a49f8504c1793e1f |
completed | March 27, 2026, 7:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c77551f85881909893d67176ee5556 |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:32 p.m.