Triple
T17255892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hope Logan |
E418878
|
entity |
| Predicate | aunt |
P3525
|
FINISHED |
| Object | Donna Logan |
E1259896
|
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: Donna Logan | Statement: [Hope Logan, aunt, Donna Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donna Logan Context triple: [Hope Logan, aunt, Donna Logan]
-
A.
Donna Logan
chosen
Donna Logan is a fictional character from the soap opera "The Bold and the Beautiful," known as a member of the Logan family and for her dramatic romantic and family storylines.
-
B.
Roberta Logan
Roberta Logan is a fictional character appearing in the mystery film "Mr. Wong in Chinatown."
-
C.
Arlene Donovan
Arlene Donovan is a film producer best known for her work on the acclaimed 1984 drama "Places in the Heart."
-
D.
Jacqueline Logan
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
E.
Donna Douglas
Donna Douglas was an American actress and singer best known for her role as Elly May Clampett on the classic television sitcom "The Beverly Hillbillies."
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6ceb9c8190a4eeaf10e90cd5a0 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c3ca3f08190b7da411a5638214e |
completed | May 11, 2026, 7:58 a.m. |
Created at: April 10, 2026, 5:39 a.m.