Triple
T1093916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parry Sound |
E24227
|
entity |
| Predicate | distanceFromToronto |
P23803
|
FINISHED |
| Object | approximately 225 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 225 kilometres | Statement: [Parry Sound, distanceFromToronto, approximately 225 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromToronto Context triple: [Parry Sound, distanceFromToronto, approximately 225 kilometres]
-
A.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
-
B.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
C.
distanceFromSanFrancisco
Indicates the measured distance between a given entity’s location and the city of San Francisco.
-
D.
distanceToLosAngeles
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
-
E.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.