Triple
T21732251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto Rock |
E536434
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Jamie Dawick |
—
|
NE NERFINISHED |
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: Jamie Dawick | Statement: [Toronto Rock, owner, Jamie Dawick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamie Dawick Context triple: [Toronto Rock, owner, Jamie Dawick]
-
A.
Jamie Dawick
chosen
Jamie Dawick is a Canadian businessman best known as the longtime owner and governor of the National Lacrosse League’s Toronto Rock.
-
B.
Douglas Dawson
Douglas Dawson was the husband of American film actress Jean Parker, known primarily in relation to her personal life.
-
C.
Max Dennison
Max Dennison is the skeptical teenage protagonist of the Halloween-themed fantasy film "Hocus Pocus," whose actions accidentally resurrect three witches in Salem.
-
D.
Lee Crocker
Lee Crocker is a software engineer and developer known for his contributions to early web technologies and open-source projects.
-
E.
Michael Dugdale
Michael Dugdale is a central character in the British conspiracy thriller series "Utopia," depicted as a morally conflicted civil servant entangled in a vast and sinister global plot.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd085eec81908b3df82bc25a8780 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 16, 2026, 6:48 p.m.