Triple
T19740072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dauphin, Manitoba |
E474090
|
entity |
| Predicate | distanceToBrandon |
P137154
|
FINISHED |
| Object | approximately 145 kilometres north |
—
|
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 145 kilometres north | Statement: [Dauphin, Manitoba, distanceToBrandon, approximately 145 kilometres north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBrandon Context triple: [Dauphin, Manitoba, distanceToBrandon, approximately 145 kilometres north]
-
A.
distanceToBray
Indicates the spatial distance between a given entity and the location named Bray.
-
B.
distanceToJackson
Indicates the spatial distance or separation between a given entity and Jackson.
-
C.
distanceToBristol
Indicates the measured or calculated spatial distance between a given entity and the location of Bristol.
-
D.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
E.
distanceToDetroit
Indicates the measured or calculated spatial distance between a given entity and the location of Detroit.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e651607e388190bbb2aaed252820fe |
completed | April 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:47 p.m.