Triple
T5421276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YHM |
E121254
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Toronto, Ontario |
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, Ontario | Statement: [YHM, nearbyCity, Toronto, Ontario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toronto, Ontario Context triple: [YHM, nearbyCity, Toronto, Ontario]
-
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.
Ottawa
Ottawa are an Algonquian-speaking Indigenous people of North America historically known for their role in Great Lakes trade networks and resistance to European colonial expansion.
-
D.
Aurora, Ontario
Aurora, Ontario is a suburban town in the Greater Toronto Area known for its residential communities, historic downtown, and role as a regional commercial and commuter hub.
-
E.
London, Ontario
London, Ontario is a mid-sized Canadian city in southwestern Ontario known for its educational institutions, healthcare sector, and role as a regional economic and cultural hub.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87eac41481908a4982db5d119edd |
completed | March 20, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf6c548a40819086910fbc39b21e90 |
completed | March 22, 2026, 4:13 a.m. |
Created at: March 20, 2026, 2:06 p.m.