Triple
T2926724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paddington 2 |
E78861
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Mark Everson
Mark Everson is a British film editor known for his work on acclaimed family and comedy films, including the Paddington series.
|
E311064
|
NE FINISHED |
How this triple was built (4 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: Mark Everson | Statement: [Paddington 2, editedBy, Mark Everson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Everson Context triple: [Paddington 2, editedBy, Mark Everson]
-
A.
Marc Eversley
Marc Eversley is a Canadian basketball executive known for serving as the general manager of the NBA’s Chicago Bulls.
-
B.
Stephen Evans
Stephen Evans is a British film producer best known for his work on acclaimed literary and period adaptations, including the 1993 film "Much Ado About Nothing."
-
C.
Dan Janvey
Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
-
D.
Michael Evans
Michael Evans is a smart, socially conscious teenage son in the 1970s sitcom "Good Times," often serving as the show's outspoken voice on political and racial issues.
-
E.
Michael Andrews
Michael Andrews is an American film composer and musician known for his atmospheric scores for movies such as Donnie Darko and Bridesmaids.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mark Everson Triple: [Paddington 2, editedBy, Mark Everson]
Generated description
Mark Everson is a British film editor known for his work on acclaimed family and comedy films, including the Paddington series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Everson Target entity description: Mark Everson is a British film editor known for his work on acclaimed family and comedy films, including the Paddington series.
-
A.
Marc Eversley
Marc Eversley is a Canadian basketball executive known for serving as the general manager of the NBA’s Chicago Bulls.
-
B.
Stephen Evans
Stephen Evans is a British film producer best known for his work on acclaimed literary and period adaptations, including the 1993 film "Much Ado About Nothing."
-
C.
Dan Janvey
Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
-
D.
Michael Evans
Michael Evans is a smart, socially conscious teenage son in the 1970s sitcom "Good Times," often serving as the show's outspoken voice on political and racial issues.
-
E.
Michael Andrews
Michael Andrews is an American film composer and musician known for his atmospheric scores for movies such as Donnie Darko and Bridesmaids.
- F. None of above. chosen
Provenance (5 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97c1e9c08190bcec80bc3262697a |
completed | March 8, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08668a204819082b13e6ce62d5728 |
completed | March 10, 2026, 9 p.m. |
| NEDg | Description generation | batch_69b0d18f7928819098fba6a23dd40230 |
completed | March 11, 2026, 2:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0d221ec2481909c9d42f1c0d86b9b |
completed | March 11, 2026, 2:23 a.m. |
Created at: March 8, 2026, 2:55 p.m.