Triple
T24741548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morrisburg, Ontario |
E618574
|
entity |
| Predicate | distanceFromOttawaApproxKm |
P23261
|
FINISHED |
| Object | 80 |
—
|
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: 80 | Statement: [Morrisburg, Ontario, distanceFromOttawaApproxKm, 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromOttawaApproxKm Context triple: [Morrisburg, Ontario, distanceFromOttawaApproxKm, 80]
-
A.
distanceToOttawa
chosen
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
-
B.
distanceToOttawaByRoad
Indicates the length of the travel route between a place and Ottawa when moving along the road network rather than in a straight line.
-
C.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
D.
distanceToGatineauByRoad_km
Indicates the length, in kilometers, of the road route needed to travel from an entity to Gatineau.
-
E.
distanceFromGatineau
Indicates the spatial distance between a given entity or location and the city of Gatineau.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 4:14 a.m.