Triple
T537426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elia Kazan |
E12355
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Frances Rudge
Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
|
E180384
|
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: Frances Rudge | Statement: [Elia Kazan, spouse, Frances Rudge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frances Rudge Context triple: [Elia Kazan, spouse, Frances Rudge]
-
A.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
B.
Louise Whitfield
Louise Whitfield was an American philanthropist best known as the wife of industrialist Andrew Carnegie and for her extensive charitable work.
-
C.
Harriet Eckersall
Harriet Eckersall was the wife of the influential British economist and demographer Thomas Robert Malthus.
-
D.
Joan Barclay
Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
-
E.
June Rowlands
June Rowlands was a Canadian politician who became the first woman to serve as mayor of Toronto, leading the city in the early 1990s.
- 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: Frances Rudge Triple: [Elia Kazan, spouse, Frances Rudge]
Generated description
Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frances Rudge Target entity description: Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
-
A.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
B.
Louise Whitfield
Louise Whitfield was an American philanthropist best known as the wife of industrialist Andrew Carnegie and for her extensive charitable work.
-
C.
Harriet Eckersall
Harriet Eckersall was the wife of the influential British economist and demographer Thomas Robert Malthus.
-
D.
Joan Barclay
Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
-
E.
June Rowlands
June Rowlands was a Canadian politician who became the first woman to serve as mayor of Toronto, leading the city in the early 1990s.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a496dc0aac8190afb75ec6c47a1d2d |
completed | March 1, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4678de4481908d6a0e6325e0a0e0 |
completed | March 8, 2026, 9:50 a.m. |
| NEDg | Description generation | batch_69ad4774fc5c8190952196df8f618bc9 |
completed | March 8, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad47a5f5048190bc2201911e47021d |
completed | March 8, 2026, 9:55 a.m. |
Created at: March 1, 2026, 7:32 p.m.