Triple
T11985533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Short |
E285266
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object |
Michael Short
Michael Short is a Canadian comedy writer and producer known for his work on sketch shows and sitcoms, and as the brother of comedian Martin Short.
|
E958335
|
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 Short | Statement: [Martin Short, sibling, Michael Short]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Short Context triple: [Martin Short, sibling, Michael Short]
-
A.
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."
-
B.
Michael Snodgrass
Michael Snodgrass is a person notable enough to be recognized as a bearer of the surname Snodgrass.
-
C.
Michael English
Michael English is an American contemporary Christian and Southern gospel singer known for his powerful vocals and successful solo career in Christian music.
-
D.
Michael Small
Michael Small was an American film composer best known for his suspenseful and atmospheric scores for 1970s and 1980s thrillers.
-
E.
Michael Lyons
Michael Lyons is a British public servant and former chairman of the BBC Trust, known for his leadership roles in local government and public sector organizations.
- 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 Short Triple: [Martin Short, sibling, Michael Short]
Generated description
Michael Short is a Canadian comedy writer and producer known for his work on sketch shows and sitcoms, and as the brother of comedian Martin Short.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Short Target entity description: Michael Short is a Canadian comedy writer and producer known for his work on sketch shows and sitcoms, and as the brother of comedian Martin Short.
-
A.
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."
-
B.
Michael Snodgrass
Michael Snodgrass is a person notable enough to be recognized as a bearer of the surname Snodgrass.
-
C.
Michael English
Michael English is an American contemporary Christian and Southern gospel singer known for his powerful vocals and successful solo career in Christian music.
-
D.
Michael Small
Michael Small was an American film composer best known for his suspenseful and atmospheric scores for 1970s and 1980s thrillers.
-
E.
Michael Lyons
Michael Lyons is a British public servant and former chairman of the BBC Trust, known for his leadership roles in local government and public sector organizations.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47237c23081909044388ff5dc73b3 |
completed | May 1, 2026, 9:28 a.m. |
| NEDg | Description generation | batch_69f47b7c5af08190ab0bff1232530a0c |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47dd51e648190bddd41766221e22d |
completed | May 1, 2026, 10:17 a.m. |
Created at: April 8, 2026, 9:46 p.m.