Triple
T5317679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dixon of Dock Green |
E121590
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Geoffrey Adams
Geoffrey Adams is an actor known for his role in the long-running British television police drama "Dixon of Dock Green."
|
E525141
|
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: Geoffrey Adams | Statement: [Dixon of Dock Green, starring, Geoffrey Adams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Adams Context triple: [Dixon of Dock Green, starring, Geoffrey Adams]
-
A.
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.
-
B.
Geoffrey Gardner
Geoffrey Gardner is a sports administrator best known for his leadership role as a vice president within World Athletics, the international governing body for track and field.
-
C.
Geoffrey Lawrence
Geoffrey Lawrence was a British judge best known for serving as the presiding judge at the Nuremberg war crimes trials after World War II.
-
D.
Geoffrey Unsworth
Geoffrey Unsworth was a renowned British cinematographer celebrated for his visually rich work on numerous classic films of the 1960s and 1970s.
-
E.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
- 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: Geoffrey Adams Triple: [Dixon of Dock Green, starring, Geoffrey Adams]
Generated description
Geoffrey Adams is an actor known for his role in the long-running British television police drama "Dixon of Dock Green."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Adams Target entity description: Geoffrey Adams is an actor known for his role in the long-running British television police drama "Dixon of Dock Green."
-
A.
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.
-
B.
Geoffrey Gardner
Geoffrey Gardner is a sports administrator best known for his leadership role as a vice president within World Athletics, the international governing body for track and field.
-
C.
Geoffrey Lawrence
Geoffrey Lawrence was a British judge best known for serving as the presiding judge at the Nuremberg war crimes trials after World War II.
-
D.
Geoffrey Unsworth
Geoffrey Unsworth was a renowned British cinematographer celebrated for his visually rich work on numerous classic films of the 1960s and 1970s.
-
E.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd855269ac8190bb7a9248d04f1823 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf857b83f08190b2d575a052198ff1 |
completed | March 22, 2026, 6 a.m. |
| NEDg | Description generation | batch_69bf864a97fc8190874fbe65add98f72 |
completed | March 22, 2026, 6:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf8696d57881908801fda7de349561 |
completed | March 22, 2026, 6:05 a.m. |
Created at: March 20, 2026, 1:59 p.m.