Triple
T14476512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beckett on Film: Play |
E358986
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Michael Colgan
Michael Colgan is an Irish theatre and film producer best known for his extensive work staging and adapting the plays of Samuel Beckett.
|
E1106239
|
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: Michael Colgan | Statement: [Beckett on Film: Play, producer, Michael Colgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Colgan Context triple: [Beckett on Film: Play, producer, Michael Colgan]
-
A.
Michael Colgan
Michael Colgan is an actor best known for his role in the science fiction film "Donovan's Brain."
-
B.
Tim McClelland
Tim McClelland is a former Major League Baseball umpire known for his long tenure, distinctive strike zone, and involvement in several high-profile postseason games.
-
C.
Michael Coulson
Michael Coulson was the husband of American actor and early film star Conrad Nagel.
-
D.
Michael Boughen
Michael Boughen is a film producer known for his work on action and thriller movies, including the Jason Statham–starring film "Killer Elite."
-
E.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
- 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: Michael Colgan Triple: [Beckett on Film: Play, producer, Michael Colgan]
Generated description
Michael Colgan is an Irish theatre and film producer best known for his extensive work staging and adapting the plays of Samuel Beckett.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Colgan Target entity description: Michael Colgan is an Irish theatre and film producer best known for his extensive work staging and adapting the plays of Samuel Beckett.
-
A.
Michael Colgan
Michael Colgan is an actor best known for his role in the science fiction film "Donovan's Brain."
-
B.
Tim McClelland
Tim McClelland is a former Major League Baseball umpire known for his long tenure, distinctive strike zone, and involvement in several high-profile postseason games.
-
C.
Michael Coulson
Michael Coulson was the husband of American actor and early film star Conrad Nagel.
-
D.
Michael Boughen
Michael Boughen is a film producer known for his work on action and thriller movies, including the Jason Statham–starring film "Killer Elite."
-
E.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9248edb48190a74eb032aeaac027 |
completed | April 14, 2026, 7:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aaaf74481909aeda3627bea39a9 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8bd70488819083f40c38575f3071 |
completed | May 8, 2026, 7:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8d4f2e848190a3c4c423c0ffed50 |
completed | May 8, 2026, 7:14 a.m. |
Created at: April 10, 2026, 1:20 a.m.