Triple
T10558105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Griffin Ondaatje |
E249140
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Linda Spalding |
E244909
|
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: Linda Spalding | Statement: [Griffin Ondaatje, relative, Linda Spalding]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Spalding Context triple: [Griffin Ondaatje, relative, Linda Spalding]
-
A.
Linda Spalding
chosen
Linda Spalding is a Canadian-American writer and editor known for her award-winning fiction and non-fiction, including works that explore history, identity, and moral complexity.
-
B.
Linda Fratianne
Linda Fratianne is an American former figure skater and two-time world champion who was one of the sport’s leading ladies in the late 1970s.
-
C.
Lindsey Chapman
Lindsey Chapman is a British television and radio presenter best known for her work on nature and wildlife programmes.
-
D.
Shannon Spake
Shannon Spake is an American sportscaster and television personality best known for her work covering NASCAR and other sports for major networks such as Fox Sports.
-
E.
Lindy Booth
Lindy Booth is a Canadian actress known for her roles in television series and films, particularly in genre and adventure projects.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5271521a4819086d96e1f183ab07a |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b38b4c081908cc2816144c23152 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:35 p.m.