Triple
T2572335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UP Express at Union Station |
E57691
|
entity |
| Predicate | distanceToTorontoPearsonInternationalAirport |
P39870
|
FINISHED |
| Object | approximately 23 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: approximately 23 kilometres | Statement: [UP Express at Union Station, distanceToTorontoPearsonInternationalAirport, approximately 23 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTorontoPearsonInternationalAirport Context triple: [UP Express at Union Station, distanceToTorontoPearsonInternationalAirport, approximately 23 kilometres]
-
A.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
B.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
C.
distanceToOttawa
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
-
D.
distanceToWinnipeg
Indicates the spatial distance between a given entity’s location and the city of Winnipeg.
-
E.
distanceToThunderBay
Indicates the physical distance between a given location or entity and Thunder Bay.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3853c848190970e8a2da16d726d |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:48 p.m.