Triple
T7726966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Watkins |
E175154
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sean Watkins |
E175154
|
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: Sean Watkins | Statement: [Sean Watkins, name, Sean Watkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Watkins Context triple: [Sean Watkins, name, Sean Watkins]
-
A.
Sean Watkins
chosen
Sean Watkins is an American guitarist, singer, and songwriter best known as a founding member of the progressive bluegrass band Nickel Creek.
-
B.
Joel McNeely
Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
-
C.
Joel O’Brien
Joel O’Brien is a musician known for his work featured on the album "Tapestry."
-
D.
Josh Dylan
Josh Dylan is a British actor best known for his role as young Bill in the film "Mamma Mia! Here We Go Again."
-
E.
Christopher Young
Christopher Young is an American film composer renowned for his atmospheric and often darkly dramatic scores across horror, thriller, and action movies.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70314abb88190a7eaa519bd7398c9 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8d6b1f7648190a0e2fd82ecb9c8b9 |
completed | March 29, 2026, 7:37 a.m. |
Created at: March 27, 2026, 4:06 p.m.