Triple
T17415106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Howard |
E423468
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Sally Beauman
Sally Beauman was a British journalist and bestselling novelist known for works such as "Rebecca’s Tale" and "Destiny."
|
E1337726
|
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: Sally Beauman | Statement: [Alan Howard, spouse, Sally Beauman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sally Beauman Context triple: [Alan Howard, spouse, Sally Beauman]
-
A.
Belinda Bauer
Belinda Bauer is a British crime novelist acclaimed for her psychologically rich thrillers and multiple major crime-writing awards.
-
B.
Belinda Bauer
Belinda Bauer is an Australian actress best known for her film and television roles in the 1980s and early 1990s, often in thrillers and science fiction projects.
-
C.
Cathryn Bradshaw
Cathryn Bradshaw is a British actress known for her work in film, television, and theatre, including roles in productions such as the 2006 drama "Venus."
-
D.
Sally Bretton
Sally Bretton is an English actress best known for her television roles in series such as "Not Going Out" and "Green Wing."
-
E.
Helen McDougall
Helen McDougall, better known by her stage name Helen Mack, was an American actress who appeared in films, radio, and early television during the 1930s and 1940s.
- 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: Sally Beauman Triple: [Alan Howard, spouse, Sally Beauman]
Generated description
Sally Beauman was a British journalist and bestselling novelist known for works such as "Rebecca’s Tale" and "Destiny."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sally Beauman Target entity description: Sally Beauman was a British journalist and bestselling novelist known for works such as "Rebecca’s Tale" and "Destiny."
-
A.
Belinda Bauer
Belinda Bauer is a British crime novelist acclaimed for her psychologically rich thrillers and multiple major crime-writing awards.
-
B.
Belinda Bauer
Belinda Bauer is an Australian actress best known for her film and television roles in the 1980s and early 1990s, often in thrillers and science fiction projects.
-
C.
Cathryn Bradshaw
Cathryn Bradshaw is a British actress known for her work in film, television, and theatre, including roles in productions such as the 2006 drama "Venus."
-
D.
Sally Bretton
Sally Bretton is an English actress best known for her television roles in series such as "Not Going Out" and "Green Wing."
-
E.
Helen McDougall
Helen McDougall, better known by her stage name Helen Mack, was an American actress who appeared in films, radio, and early television during the 1930s and 1940s.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44231e29881909695a33aab1d49a2 |
completed | April 19, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052334e9708190ba9900fb364023ef |
completed | May 14, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_6a0527049428819080f2cc75c5223fb7 |
completed | May 14, 2026, 1:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052765e8f88190b8db3cffb212002f |
completed | May 14, 2026, 1:37 a.m. |
Created at: April 10, 2026, 5:46 a.m.