Triple
T858716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Samuel Rogers Jr. |
E18551
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object |
Velma Melissa Rogers
Velma Melissa Rogers is a member of the prominent Rogers family of Canadian broadcasting, known as the mother of media executive Edward Samuel Rogers Jr.
|
E111938
|
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: Velma Melissa Rogers | Statement: [Edward Samuel Rogers Jr., parent, Velma Melissa Rogers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velma Melissa Rogers Context triple: [Edward Samuel Rogers Jr., parent, Velma Melissa Rogers]
-
A.
Leslie
Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
-
B.
Leslie
Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
-
C.
Leslie
Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
-
D.
Vivian Lake Brady
Vivian Lake Brady is the daughter of NFL quarterback Tom Brady and supermodel Gisele Bündchen.
-
E.
Marla Maples
Marla Maples is an American actress and television personality best known for her high-profile marriage to businessman and future U.S. President Donald Trump in the 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: Velma Melissa Rogers Triple: [Edward Samuel Rogers Jr., parent, Velma Melissa Rogers]
Generated description
Velma Melissa Rogers is a member of the prominent Rogers family of Canadian broadcasting, known as the mother of media executive Edward Samuel Rogers Jr.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Velma Melissa Rogers Target entity description: Velma Melissa Rogers is a member of the prominent Rogers family of Canadian broadcasting, known as the mother of media executive Edward Samuel Rogers Jr.
-
A.
Leslie
Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
-
B.
Leslie
Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
-
C.
Leslie
Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
-
D.
Vivian Lake Brady
Vivian Lake Brady is the daughter of NFL quarterback Tom Brady and supermodel Gisele Bündchen.
-
E.
Marla Maples
Marla Maples is an American actress and television personality best known for her high-profile marriage to businessman and future U.S. President Donald Trump in the 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac4f740881909cb59a6c18a77af3 |
completed | March 1, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a93398a6948190981e932178aee6b9 |
completed | March 5, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69a93d2162ac81908830459d0c937093 |
completed | March 5, 2026, 8:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a95d2e3d908190afa636dcde6db627 |
completed | March 5, 2026, 10:38 a.m. |
Created at: March 1, 2026, 7:39 p.m.