Triple
T971519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saving Mr. Banks |
E20954
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Ian Collie
Ian Collie is a film and television producer best known for his work on the biographical drama "Saving Mr. Banks."
|
E213556
|
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: Ian Collie | Statement: [Saving Mr. Banks, producer, Ian Collie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ian Collie Context triple: [Saving Mr. Banks, producer, Ian Collie]
-
A.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
-
B.
Colin Goudie
Colin Goudie is a film editor known for his work on major feature films, including the fantasy action movie "King Arthur: Legend of the Sword."
-
C.
Garth Stevenson
Garth Stevenson is a Canadian-born double bassist and composer known for his atmospheric, nature-inspired film scores and solo work.
-
D.
Geoffrey Beevers
Geoffrey Beevers is a British actor best known to Doctor Who fans for his chilling portrayal of the villainous Time Lord known as the Master.
-
E.
James Collip
James Collip was a Canadian biochemist best known as a key member of the team that developed insulin as a treatment for diabetes.
- 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: Ian Collie Triple: [Saving Mr. Banks, producer, Ian Collie]
Generated description
Ian Collie is a film and television producer best known for his work on the biographical drama "Saving Mr. Banks."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ian Collie Target entity description: Ian Collie is a film and television producer best known for his work on the biographical drama "Saving Mr. Banks."
-
A.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
-
B.
Colin Goudie
Colin Goudie is a film editor known for his work on major feature films, including the fantasy action movie "King Arthur: Legend of the Sword."
-
C.
Garth Stevenson
Garth Stevenson is a Canadian-born double bassist and composer known for his atmospheric, nature-inspired film scores and solo work.
-
D.
Geoffrey Beevers
Geoffrey Beevers is a British actor best known to Doctor Who fans for his chilling portrayal of the villainous Time Lord known as the Master.
-
E.
James Collip
James Collip was a Canadian biochemist best known as a key member of the team that developed insulin as a treatment for diabetes.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b44aa6088190a90c44a8f694ec41 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeab03e388190b7b5c7c5802bf3c1 |
completed | March 8, 2026, 9:31 p.m. |
| NEDg | Description generation | batch_69adeb8a0a64819087e4505089e93093 |
completed | March 8, 2026, 9:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adec6fcaac8190b43d0cd1aa613c95 |
completed | March 8, 2026, 9:38 p.m. |
Created at: March 1, 2026, 7:40 p.m.