Triple
T4981744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton, Ontario |
E111901
|
entity |
| Predicate | distanceFromTorontoDowntown |
P1299
|
FINISHED |
| Object | approximately 40 kilometres |
—
|
LITERAL 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: approximately 40 kilometres | Statement: [Milton, Ontario, distanceFromTorontoDowntown, approximately 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTorontoDowntown Context triple: [Milton, Ontario, distanceFromTorontoDowntown, approximately 40 kilometres]
-
A.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
B.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
C.
distanceToTorontoPearsonInternationalAirport
Indicates the physical distance between a given location and Toronto Pearson International Airport.
-
D.
distanceToOttawa
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
-
E.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
- F. None of above.
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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.