Triple
T17313562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Ono |
E420361
|
entity |
| Predicate | hasDoctoralStudent |
P20123
|
FINISHED |
| Object |
Amanda Folsom
Amanda Folsom is an American mathematician known for her work in number theory and modular forms.
|
E1399447
|
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: Amanda Folsom | Statement: [Ken Ono, hasDoctoralStudent, Amanda Folsom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Folsom Context triple: [Ken Ono, hasDoctoralStudent, Amanda Folsom]
-
A.
Amanda Woodward
Amanda Woodward is a powerful, manipulative advertising executive and one of the central, iconic characters on the 1990s TV drama "Melrose Place."
-
B.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
C.
Amanda Naughton
Amanda Naughton is an American actress best known for her starring role on the 1990s television series "Remember WENN."
-
D.
Jennifer Bransford
Jennifer Bransford is an American actress best known for her work in television soap operas and other TV roles.
-
E.
Emily Friehl
Emily Friehl is a free-spirited, aspiring actress and photographer who forms a years-long, will-they-won’t-they romantic connection with Oliver in the film "A Lot Like Love."
- 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: Amanda Folsom Triple: [Ken Ono, hasDoctoralStudent, Amanda Folsom]
Generated description
Amanda Folsom is an American mathematician known for her work in number theory and modular forms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amanda Folsom Target entity description: Amanda Folsom is an American mathematician known for her work in number theory and modular forms.
-
A.
Amanda Woodward
Amanda Woodward is a powerful, manipulative advertising executive and one of the central, iconic characters on the 1990s TV drama "Melrose Place."
-
B.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
C.
Amanda Naughton
Amanda Naughton is an American actress best known for her starring role on the 1990s television series "Remember WENN."
-
D.
Jennifer Bransford
Jennifer Bransford is an American actress best known for her work in television soap operas and other TV roles.
-
E.
Emily Friehl
Emily Friehl is a free-spirited, aspiring actress and photographer who forms a years-long, will-they-won’t-they romantic connection with Oliver in the film "A Lot Like Love."
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4399a4194819091d34cd3fffc8072 |
completed | April 19, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dba6fd6481909fdfb630a195d57e |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dce009a48190ad0a2bb48e49002a |
completed | May 16, 2026, 2:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07dd57f9548190b6b7e909eccbbfa9 |
completed | May 16, 2026, 2:58 a.m. |
Created at: April 10, 2026, 5:43 a.m.