Triple
T14241681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doria Ragland |
E353022
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Doria Ragland |
E353022
|
NE FINISHED |
How this triple was built (2 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: Doria Ragland | Statement: [Doria Ragland, name, Doria Ragland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doria Ragland Context triple: [Doria Ragland, name, Doria Ragland]
-
A.
Doria Ragland
chosen
Doria Ragland is an American social worker, yoga instructor, and former makeup artist best known as the mother of Meghan, Duchess of Sussex.
-
B.
Isabel Scott Rorick
Isabel Scott Rorick was an American author best known for her humorous "Mr. and Mrs. Cugat" stories, which inspired the radio and television series "My Favorite Husband."
-
C.
Audra Lindley
Audra Lindley was an American actress best known for her role as the quirky landlady Helen Roper on the television sitcom "Three's Company" and its spin-off "The Ropers."
-
D.
Lucinda Franks
Lucinda Franks was a Pulitzer Prize–winning American journalist and author known for her investigative reporting and memoirs.
-
E.
Annmarie Fulton
Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6244ad188190b9d9db7914240410 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda904f8ac8190a4206b6ab6ee812c |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 10, 2026, 1:08 a.m.