Triple
T10310821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Heflin |
E241883
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Frances Neal
Frances Neal was an American actress best known for her work in the 1930s and 1940s and for her marriage to actor Van Heflin.
|
E868893
|
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 Neal | Statement: [Van Heflin, spouse, Frances Neal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frances Neal Context triple: [Van Heflin, spouse, Frances Neal]
-
A.
Frances Bavier
Frances Bavier was an American actress best known for her portrayal of the warm but no-nonsense Aunt Bee on the classic television sitcom "The Andy Griffith Show."
-
B.
Ruth Wells
Ruth Wells was the wife of three-time Academy Award–winning American character actor Walter Brennan.
-
C.
Myrna Fahey
Myrna Fahey was an American actress known for her film and television roles in the 1950s and 1960s, often appearing in comedies and dramas.
-
D.
Josephine Dunn
Josephine Dunn was an American film and stage actress of the late silent and early sound era, known for her roles in musical and dramatic pictures of the 1920s and 1930s.
-
E.
Mary Wickes
Mary Wickes was an American character actress known for her sharp-tongued, comedic roles in film and television across several decades.
- 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 Neal Triple: [Van Heflin, spouse, Frances Neal]
Generated description
Frances Neal was an American actress best known for her work in the 1930s and 1940s and for her marriage to actor Van Heflin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frances Neal Target entity description: Frances Neal was an American actress best known for her work in the 1930s and 1940s and for her marriage to actor Van Heflin.
-
A.
Frances Bavier
Frances Bavier was an American actress best known for her portrayal of the warm but no-nonsense Aunt Bee on the classic television sitcom "The Andy Griffith Show."
-
B.
Ruth Wells
Ruth Wells was the wife of three-time Academy Award–winning American character actor Walter Brennan.
-
C.
Myrna Fahey
Myrna Fahey was an American actress known for her film and television roles in the 1950s and 1960s, often appearing in comedies and dramas.
-
D.
Josephine Dunn
Josephine Dunn was an American film and stage actress of the late silent and early sound era, known for her roles in musical and dramatic pictures of the 1920s and 1930s.
-
E.
Mary Wickes
Mary Wickes was an American character actress known for her sharp-tongued, comedic roles in film and television across several decades.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d32ac6c08190b23eb042b3ec284a |
completed | April 7, 2026, 9:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d66ae248190b8af31b032f9f857 |
completed | April 10, 2026, 2:47 p.m. |
| NEDg | Description generation | batch_69d9107c75108190994939ab46aa642f |
completed | April 10, 2026, 3 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9154c922c81909991f87f89c083cd |
completed | April 10, 2026, 3:20 p.m. |
Created at: April 6, 2026, 11:47 a.m.