Triple
T14739866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wakefield, Quebec |
E346315
|
entity |
| Predicate | distanceToGatineauByRoad_km |
P115579
|
FINISHED |
| Object | approximately 25 |
—
|
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 25 | Statement: [Wakefield, Quebec, distanceToGatineauByRoad_km, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGatineauByRoad_km Context triple: [Wakefield, Quebec, distanceToGatineauByRoad_km, approximately 25]
-
A.
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.
-
B.
distanceToMontreal
Indicates the spatial distance between a given entity’s location and the city of Montreal.
-
C.
distanceToOttawa
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
-
D.
distanceFromQuebecCityCentre
Indicates the measured spatial distance between a given location and the center of Quebec City.
-
E.
distanceToVancouverByRoad
Indicates the length of the route required to travel by road from a given place to Vancouver.
- F. None of above. chosen
Provenance (4 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7345680819093e901233a064e48 |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:29 a.m.