Triple
T993432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giller Prize |
E21442
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Toronto |
E1525
|
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: Toronto | Statement: [Giller Prize, location, Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toronto Context triple: [Giller Prize, location, Toronto]
-
A.
Toronto
chosen
Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
-
B.
Ottawa
Ottawa is the capital city of Canada, located in eastern Ontario along the Ottawa River and known for its federal government institutions, cultural landmarks, and bilingual character.
-
C.
North York
North York is a major district in the north end of Toronto, Ontario, known for its dense urban development, shopping centers, and mixed residential and commercial areas.
-
D.
Downtown Toronto
Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
-
E.
PortsToronto
PortsToronto is a government business enterprise that manages and operates key transportation and waterfront assets in Toronto, including Billy Bishop Toronto City Airport and the city’s port and marina facilities.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c5e16881908cd5f7ba2fcd5084 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac762a53b48190a4d98b0416b4697c |
completed | March 7, 2026, 7:02 p.m. |
Created at: March 1, 2026, 7:41 p.m.