Triple
T21792969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dora Wheeler |
E538021
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
Candace Wheeler
Candace Wheeler was a pioneering American interior and textile designer often regarded as one of the first prominent female professional designers in the United States.
|
E1552088
|
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: Candace Wheeler | Statement: [Dora Wheeler, mother, Candace Wheeler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Candace Wheeler Context triple: [Dora Wheeler, mother, Candace Wheeler]
-
A.
Candace Faulkner
Candace Faulkner is known as the former spouse of American actor and screenwriter Robert Culp.
-
B.
Candace Fisher
Candace Fisher is best known as the former wife of retired NBA player and coach Derek Fisher.
-
C.
Candice Nelson
Candice Nelson is an American songwriter and producer known for crafting R&B and pop hits for major artists in the 2000s.
-
D.
Candace Young
Candace Young is a central, scheming yet complex character in Tyler Perry’s drama series "The Haves and the Have Nots," known for her ambition, manipulation, and troubled personal life.
-
E.
Candy Toxton
Candy Toxton was an American actress and model active in the late 1940s, known for a handful of film appearances before retiring from show business.
- 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: Candace Wheeler Triple: [Dora Wheeler, mother, Candace Wheeler]
Generated description
Candace Wheeler was a pioneering American interior and textile designer often regarded as one of the first prominent female professional designers in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Candace Wheeler Target entity description: Candace Wheeler was a pioneering American interior and textile designer often regarded as one of the first prominent female professional designers in the United States.
-
A.
Candace Faulkner
Candace Faulkner is known as the former spouse of American actor and screenwriter Robert Culp.
-
B.
Candace Fisher
Candace Fisher is best known as the former wife of retired NBA player and coach Derek Fisher.
-
C.
Candice Nelson
Candice Nelson is an American songwriter and producer known for crafting R&B and pop hits for major artists in the 2000s.
-
D.
Candace Young
Candace Young is a central, scheming yet complex character in Tyler Perry’s drama series "The Haves and the Have Nots," known for her ambition, manipulation, and troubled personal life.
-
E.
Candy Toxton
Candy Toxton was an American actress and model active in the late 1940s, known for a handful of film appearances before retiring from show business.
- 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_69e0c47198f881908cb0d237266c10e9 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f06221d1f4819089bb113d808d79c2 |
completed | April 28, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b8fabf9fc81909cb79b5caa7d5312 |
completed | May 18, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_6a0b90cfe3108190bbf69c9a6041399e |
completed | May 18, 2026, 10:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9163f1b481908cc4091b389bced4 |
completed | May 18, 2026, 10:23 p.m. |
Created at: April 16, 2026, 6:52 p.m.