Triple
T9347989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbotsford |
E224940
|
entity |
| Predicate | distanceToVancouver |
P88076
|
FINISHED |
| Object | about 70 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: about 70 kilometres | Statement: [Abbotsford, distanceToVancouver, about 70 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVancouver Context triple: [Abbotsford, distanceToVancouver, about 70 kilometres]
-
A.
distanceToVancouverByRoad
Indicates the length of the route required to travel by road from a given place to Vancouver.
-
B.
distanceToTofino_km
Indicates the distance, measured in kilometers, between a given location and Tofino.
-
C.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
D.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
E.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f107f0081908938f4b814eca5fc |
completed | April 1, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:41 p.m.