Triple
T20449315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Clinic (1982 film) |
E501604
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Tom Cowan
Tom Cowan is an Australian cinematographer and filmmaker known for his work on numerous feature films and documentaries.
|
E1431649
|
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: Tom Cowan | Statement: [The Clinic (1982 film), cinematographyBy, Tom Cowan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Cowan Context triple: [The Clinic (1982 film), cinematographyBy, Tom Cowan]
-
A.
Mike Coward
Mike Coward is a distinguished figure in his field, recognized for his significant contributions that earned him the prestigious William Smith Medal.
-
B.
James Cowan
James Cowan was the husband of Australian social reformer and politician Edith Cowan, supporting her pioneering public and political work in Western Australia.
-
C.
Matthew Cowden
Matthew Cowden is an American Episcopal bishop who serves as the ecclesiastical leader of the Episcopal Diocese of West Virginia.
-
D.
Rob Cowan
Rob Cowan is a film producer known for working on major studio projects, including DC Comics adaptations.
-
E.
Elliot Cowan
Elliot Cowan is a British actor known for his work in film, television, and theatre, including roles in projects such as "Lost in Austen" and "Da Vinci's Demons."
- 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: Tom Cowan Triple: [The Clinic (1982 film), cinematographyBy, Tom Cowan]
Generated description
Tom Cowan is an Australian cinematographer and filmmaker known for his work on numerous feature films and documentaries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Cowan Target entity description: Tom Cowan is an Australian cinematographer and filmmaker known for his work on numerous feature films and documentaries.
-
A.
Mike Coward
Mike Coward is a distinguished figure in his field, recognized for his significant contributions that earned him the prestigious William Smith Medal.
-
B.
James Cowan
James Cowan was the husband of Australian social reformer and politician Edith Cowan, supporting her pioneering public and political work in Western Australia.
-
C.
Matthew Cowden
Matthew Cowden is an American Episcopal bishop who serves as the ecclesiastical leader of the Episcopal Diocese of West Virginia.
-
D.
Rob Cowan
Rob Cowan is a film producer known for working on major studio projects, including DC Comics adaptations.
-
E.
Elliot Cowan
Elliot Cowan is a British actor known for his work in film, television, and theatre, including roles in projects such as "Lost in Austen" and "Da Vinci's Demons."
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfffae4819086c727f4143c2737 |
completed | April 20, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0884080b388190aecf47ebd4ab494f |
completed | May 16, 2026, 2:49 p.m. |
| NEDg | Description generation | batch_6a08859b65b88190af28a075931fa380 |
completed | May 16, 2026, 2:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08863ed9748190bd15713b2cfa61c0 |
completed | May 16, 2026, 2:59 p.m. |
Created at: April 16, 2026, 11:32 a.m.