Triple
T15258366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandon, Manitoba |
E364706
|
entity |
| Predicate | distanceFromWinnipeg |
P38931
|
FINISHED |
| Object | approximately 200 km west |
—
|
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 200 km west | Statement: [Brandon, Manitoba, distanceFromWinnipeg, approximately 200 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromWinnipeg Context triple: [Brandon, Manitoba, distanceFromWinnipeg, approximately 200 km west]
-
A.
distanceToWinnipeg
chosen
Indicates the spatial distance between a given entity’s location and the city of Winnipeg.
-
B.
distanceFromCalgary
Indicates the spatial distance between a given location and the city of Calgary.
-
C.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
D.
distanceToEdmonton
Indicates the spatial distance between a given entity’s location and the city of Edmonton.
-
E.
distanceFromTimmins
Indicates the measured distance between a given location or entity and the reference location Timmins.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:13 a.m.