Triple
T28934705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Renfrew |
E733881
|
entity |
| Predicate | distanceToVictoriaByRoad_km |
P202121
|
FINISHED |
| Object | approximately 110 |
—
|
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 110 | Statement: [Port Renfrew, distanceToVictoriaByRoad_km, approximately 110]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVictoriaByRoad_km Context triple: [Port Renfrew, distanceToVictoriaByRoad_km, approximately 110]
-
A.
distanceToVancouverByRoad
Indicates the length of the route required to travel by road from a given place to Vancouver.
-
B.
distanceFromVictoria
Indicates the measured distance between a given entity or location and Victoria.
-
C.
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.
-
D.
distanceToVancouver
Indicates the spatial distance between a given entity’s location and the city of Vancouver.
-
E.
distanceToWhistlerByRoad
Indicates the road travel distance between a given place and Whistler.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a00532815c881908f10d9594458b3d7 |
completed | May 10, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_6a0052b9f030819081b8105bdcaf6d8f |
completed | May 10, 2026, 9:41 a.m. |
| PDg | Predicate description generation | batch_6a005326c1508190ace47b84c08b9565 |
completed | May 10, 2026, 9:43 a.m. |
Created at: April 28, 2026, 8:31 a.m.