Triple
T10026017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skins |
E200725
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Bryan Elsley |
E843696
|
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: Bryan Elsley | Statement: [Skins, executiveProducer, Bryan Elsley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryan Elsley Context triple: [Skins, executiveProducer, Bryan Elsley]
-
A.
Bryan Elsley
chosen
Bryan Elsley is a Scottish television writer and producer best known for co-creating the groundbreaking British teen drama series "Skins."
-
B.
Bryan Bedford
Bryan Bedford is an American airline executive best known for leading regional carriers such as Chautauqua Airlines and Republic Airways Holdings.
-
C.
Bryan Bedford
Bryan Bedford is the young boy central to the 1994 film "Miracle on 34th Street," whose belief in Santa Claus becomes a key focus of the story.
-
D.
Ben Esler
Ben Esler is an Australian actor best known for his roles in television dramas and historical series, including a prominent part in the Western series "Hell on Wheels."
-
E.
Bryan Southcombe
Bryan Southcombe is a New Zealand-born actor and publicist best known for his former marriage to British actress Charlotte Rampling.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcde2009081908eddda7813617df4 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30020305c81909c4fb01291c70cb6 |
completed | April 6, 2026, 12:36 a.m. |
Created at: March 30, 2026, 8:53 p.m.