Triple
T22699617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exeter, Ontario |
E561277
|
entity |
| Predicate | distanceToLondonOntario |
P8256
|
FINISHED |
| Object | approximately 50 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 50 kilometres | Statement: [Exeter, Ontario, distanceToLondonOntario, approximately 50 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLondonOntario Context triple: [Exeter, Ontario, distanceToLondonOntario, approximately 50 kilometres]
-
A.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
B.
distanceToLondon
chosen
Indicates the measured distance between a given entity’s location and the city of London.
-
C.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
D.
distanceToOttawa
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
-
E.
distanceToWindsor
Indicates the spatial distance between a given entity and the location named Windsor.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178c944748190a0712983f7059114 |
completed | April 29, 2026, 3:19 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:15 p.m.