Triple
T13667938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mad Dogs |
E327670
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Max Beesley |
E213654
|
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: Max Beesley | Statement: [Mad Dogs, portrayedBy, Max Beesley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Beesley Context triple: [Mad Dogs, portrayedBy, Max Beesley]
-
A.
Max Beesley
chosen
Max Beesley is an English actor and musician known for his roles in film and television dramas, as well as his work as a session keyboardist.
-
B.
Damon Beesley
Damon Beesley is a British television writer and producer best known for co-creating the hit comedy series "The Inbetweeners."
-
C.
Charlie Bewley
Charlie Bewley is a British actor best known for his roles in the Twilight film series and various independent films and television dramas.
-
D.
Jonathan Brackley
Jonathan Brackley is a British television writer and producer best known for co-creating and writing the sci-fi drama series "Humans."
-
E.
Jason Flemyng
Jason Flemyng is an English actor known for his character roles in films such as "Lock, Stock and Two Smoking Barrels," "Snatch," and various Hollywood and British productions.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7943bfaf0819097410e901847d77c |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:52 p.m.