Triple
T317105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Hawking |
E7730
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Elaine Mason
Elaine Mason was a British nurse who became the second wife of theoretical physicist Stephen Hawking.
|
E164012
|
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: Elaine Mason | Statement: [Stephen Hawking, spouse, Elaine Mason]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elaine Mason Context triple: [Stephen Hawking, spouse, Elaine Mason]
-
A.
Elaine Devry
Elaine Devry is an American actress known for her film and television roles in the 1950s and 1960s.
-
B.
Margo Anderson
Margo Anderson is best known as a former wife of American country music star Kenny Rogers.
-
C.
Lucille Sheardown
Lucille Sheardown was one of the later wives of American inventor Lee de Forest, associated with his personal life rather than his pioneering work in radio and electronics.
-
D.
Margo Wilson
Margo Wilson was a pioneering Canadian evolutionary psychologist best known for her influential research on violence, homicide, and parental investment, often conducted in collaboration with Martin Daly.
-
E.
Donna Tubbs
Donna Tubbs is a central character in the animated sitcom universe of Family Guy and The Cleveland Show, known as Cleveland Brown's strong-willed, caring, and often no-nonsense wife.
- 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: Elaine Mason Triple: [Stephen Hawking, spouse, Elaine Mason]
Generated description
Elaine Mason was a British nurse who became the second wife of theoretical physicist Stephen Hawking.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elaine Mason Target entity description: Elaine Mason was a British nurse who became the second wife of theoretical physicist Stephen Hawking.
-
A.
Elaine Devry
Elaine Devry is an American actress known for her film and television roles in the 1950s and 1960s.
-
B.
Margo Anderson
Margo Anderson is best known as a former wife of American country music star Kenny Rogers.
-
C.
Lucille Sheardown
Lucille Sheardown was one of the later wives of American inventor Lee de Forest, associated with his personal life rather than his pioneering work in radio and electronics.
-
D.
Margo Wilson
Margo Wilson was a pioneering Canadian evolutionary psychologist best known for her influential research on violence, homicide, and parental investment, often conducted in collaboration with Martin Daly.
-
E.
Donna Tubbs
Donna Tubbs is a central character in the animated sitcom universe of Family Guy and The Cleveland Show, known as Cleveland Brown's strong-willed, caring, and often no-nonsense wife.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea65ca7081908093e6aaaf2d34f7 |
completed | Feb. 28, 2026, 1:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad01211c2c8190bc107dae8a9ec2a2 |
completed | March 8, 2026, 4:54 a.m. |
| NEDg | Description generation | batch_69ad01f8028881909af95e9f61a17e88 |
completed | March 8, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad02c618c48190abf3e16d9f85e703 |
completed | March 8, 2026, 5:01 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.