Triple
T14460917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Skrein |
E358580
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ed Skrein |
E358580
|
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: Ed Skrein | Statement: [Ed Skrein, name, Ed Skrein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Skrein Context triple: [Ed Skrein, name, Ed Skrein]
-
A.
Ed Skrein
chosen
Ed Skrein is a British actor and rapper best known for roles in films such as "Deadpool," "The Transporter Refueled," and "Alita: Battle Angel."
-
B.
Chris Swanson
Chris Swanson is a music industry executive and co-founder of the independent record label Dead Oceans, known for its roster of acclaimed indie and alternative artists.
-
C.
Scott Adkins
Scott Adkins is an English actor and highly skilled martial artist best known for his roles in action films such as the Undisputed series and numerous high-intensity fight-driven movies.
-
D.
Jason Statham
Jason Statham is an English actor and former competitive diver best known for his tough-guy roles in high-octane action films such as The Transporter, Crank, and The Expendables franchises.
-
E.
Frank Grillo
Frank Grillo is an American actor best known for his tough, action-oriented roles in films such as the Purge series and the Marvel Cinematic Universe.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91abc1008190a19de4f8f0112c9d |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6495660081908ab9db11939e74f7 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:19 a.m.