Triple
T4195046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Phillips |
E89128
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | City of 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: City of Toronto | Statement: [Nathan Phillips, employer, City of Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Toronto Context triple: [Nathan Phillips, employer, City of 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.
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.
-
C.
City of Ontario
The City of Ontario is a major suburban city in southwestern San Bernardino County, California, known for its international airport, logistics hubs, and role as an Inland Empire commercial center.
-
D.
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.
-
E.
Greater Toronto Area
The Greater Toronto Area is a large metropolitan region in Ontario, Canada, encompassing Toronto and its surrounding municipalities and suburbs.
- 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af034406348190a56c21b5c08a6828 |
completed | March 9, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b596151b3c8190a70653747f7e3ff3 |
completed | March 14, 2026, 5:08 p.m. |
Created at: March 9, 2026, 3:46 p.m.