Triple
T9244233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peel Region |
E222146
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Caledon |
E137006
|
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: Caledon | Statement: [Peel Region, contains, Caledon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caledon Context triple: [Peel Region, contains, Caledon]
-
A.
Caledon
chosen
Caledon is a largely rural town in southern Ontario, Canada, known for its scenic landscapes and inclusion within the Greater Toronto Area.
-
B.
Etobicoke
Etobicoke is a large suburban district in the western part of Toronto, Ontario, known for its residential neighborhoods, parks, and industrial areas along the waterfront.
-
C.
Welland
Welland is a small rural village in Worcestershire, England, known for its scenic setting near the Malvern Hills.
-
D.
Welland
Welland is a city in the Niagara Region of southern Ontario, Canada, known for the Welland Canal that connects Lake Ontario and Lake Erie.
-
E.
Botwood
Botwood is a small coastal town in central Newfoundland and Labrador, Canada, historically known as a key seaport and World War II military base.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cd03edd37481908ea2f6dac354f04f |
completed | April 1, 2026, 11:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1af2542c48190b481dcd08187dabd |
completed | April 5, 2026, 12:39 a.m. |
Created at: March 30, 2026, 7:30 p.m.