Triple
T34888517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal–Quebec City |
E1006216
|
entity |
| Predicate | hasApproximateLengthKm |
P33049
|
FINISHED |
| Object | 250 |
—
|
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: 250 | Statement: [Montreal–Quebec City, hasApproximateLengthKm, 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateLengthKm Context triple: [Montreal–Quebec City, hasApproximateLengthKm, 250]
-
A.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
-
B.
depthApproxKm
Indicates the approximate depth of something measured in kilometers.
-
C.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
D.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
E.
lengthInKm
chosen
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
- F. None of above.
Provenance (3 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_69f76dbedb288190afe5780710847410 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: May 3, 2026, 4 p.m.