Triple
T34824032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farnham Common |
E1003865
|
entity |
| Predicate | distanceToBeaconsfield |
P205571
|
FINISHED |
| Object | approximately 4 miles south |
—
|
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 4 miles south | Statement: [Farnham Common, distanceToBeaconsfield, approximately 4 miles south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBeaconsfield Context triple: [Farnham Common, distanceToBeaconsfield, approximately 4 miles south]
-
A.
distanceToMontreal
Indicates the spatial distance between a given entity’s location and the city of Montreal.
-
B.
distanceFromQuebecCity
Indicates the measured distance between a given place or object and Quebec City.
-
C.
distanceFromLaval
Indicates the spatial distance between an entity and the location of Laval.
-
D.
distanceFromBarrie
Indicates the spatial distance separating something from the location of Barrie.
-
E.
distanceFromGatineau
Indicates the spatial distance between a given entity or location and the city of Gatineau.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.