Triple
T9043897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunn |
E216706
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Kaitlyn Dunn
Kaitlyn Dunn is a person notable enough to be specifically referenced as a bearer of the surname Dunn.
|
E798735
|
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: Kaitlyn Dunn | Statement: [Dunn, hasNotableBearer, Kaitlyn Dunn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaitlyn Dunn Context triple: [Dunn, hasNotableBearer, Kaitlyn Dunn]
-
A.
Kaitlyn Robrock
Kaitlyn Robrock is an American voice actress best known for portraying iconic animated characters, including serving as the current voice of Minnie Mouse for Disney.
-
B.
Katie Luber
Katie Luber is an American art museum director and curator known for leading major institutions, including the Minneapolis Institute of Art.
-
C.
Katie McNeil
Katie McNeil is an American talent manager best known for her work in the music industry and for being married to singer-songwriter Neil Diamond.
-
D.
Erin Daniels
Erin Daniels is an American actress best known for her role as Dana Fairbanks on the television drama series "The L Word."
-
E.
Lauren Dolgen
Lauren Dolgen is a television producer best known for developing and producing MTV’s teen pregnancy reality franchise, including "16 and Pregnant" and its spin-offs.
- 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: Kaitlyn Dunn Triple: [Dunn, hasNotableBearer, Kaitlyn Dunn]
Generated description
Kaitlyn Dunn is a person notable enough to be specifically referenced as a bearer of the surname Dunn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaitlyn Dunn Target entity description: Kaitlyn Dunn is a person notable enough to be specifically referenced as a bearer of the surname Dunn.
-
A.
Kaitlyn Robrock
Kaitlyn Robrock is an American voice actress best known for portraying iconic animated characters, including serving as the current voice of Minnie Mouse for Disney.
-
B.
Katie Luber
Katie Luber is an American art museum director and curator known for leading major institutions, including the Minneapolis Institute of Art.
-
C.
Katie McNeil
Katie McNeil is an American talent manager best known for her work in the music industry and for being married to singer-songwriter Neil Diamond.
-
D.
Erin Daniels
Erin Daniels is an American actress best known for her role as Dana Fairbanks on the television drama series "The L Word."
-
E.
Lauren Dolgen
Lauren Dolgen is a television producer best known for developing and producing MTV’s teen pregnancy reality franchise, including "16 and Pregnant" and its spin-offs.
- 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_69ca83d22d488190adbce5e020e9cd1d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b137cec8190bd1b812c10d9542a |
completed | April 1, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d110090f208190bf0338a37bb28e8b |
completed | April 4, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_69d110bb55488190955c18087aceecb8 |
completed | April 4, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d11113db48819083a7da54f72326a6 |
completed | April 4, 2026, 1:24 p.m. |
Created at: March 30, 2026, 7:09 p.m.