Triple
T9449852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Rampling |
E227858
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Bryan Southcombe
Bryan Southcombe is a New Zealand-born actor and publicist best known for his former marriage to British actress Charlotte Rampling.
|
E814444
|
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: Bryan Southcombe | Statement: [Charlotte Rampling, spouse, Bryan Southcombe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryan Southcombe Context triple: [Charlotte Rampling, spouse, Bryan Southcombe]
-
A.
Doug Bowne
Doug Bowne is a musician best known for his work with the new wave band Tom Tom Club.
-
B.
Bryan Bedford
Bryan Bedford is an American airline executive best known for leading regional carriers such as Chautauqua Airlines and Republic Airways Holdings.
-
C.
Bryan Bedford
Bryan Bedford is the young boy central to the 1994 film "Miracle on 34th Street," whose belief in Santa Claus becomes a key focus of the story.
-
D.
Brian Souter
Brian Souter is a Scottish businessman best known as the co-founder of the Stagecoach Group and a prominent figure in the UK transport industry.
-
E.
Geoff Pierson
Geoff Pierson is an American actor known for his work in television dramas and comedies, including prominent roles on shows like Dexter and Unhappily Ever After.
- 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: Bryan Southcombe Triple: [Charlotte Rampling, spouse, Bryan Southcombe]
Generated description
Bryan Southcombe is a New Zealand-born actor and publicist best known for his former marriage to British actress Charlotte Rampling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bryan Southcombe Target entity description: Bryan Southcombe is a New Zealand-born actor and publicist best known for his former marriage to British actress Charlotte Rampling.
-
A.
Doug Bowne
Doug Bowne is a musician best known for his work with the new wave band Tom Tom Club.
-
B.
Bryan Bedford
Bryan Bedford is an American airline executive best known for leading regional carriers such as Chautauqua Airlines and Republic Airways Holdings.
-
C.
Bryan Bedford
Bryan Bedford is the young boy central to the 1994 film "Miracle on 34th Street," whose belief in Santa Claus becomes a key focus of the story.
-
D.
Brian Souter
Brian Souter is a Scottish businessman best known as the co-founder of the Stagecoach Group and a prominent figure in the UK transport industry.
-
E.
Geoff Pierson
Geoff Pierson is an American actor known for his work in television dramas and comedies, including prominent roles on shows like Dexter and Unhappily Ever After.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f6649a48190b6844daa6202efe5 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d190cc06d48190b437edfc4fee8cce |
completed | April 4, 2026, 10:29 p.m. |
| NEDg | Description generation | batch_69d192f37e54819099d316ce44de2c81 |
completed | April 4, 2026, 10:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1933ffc3481909395c9efb63875bb |
completed | April 4, 2026, 10:40 p.m. |
Created at: March 30, 2026, 7:51 p.m.