Triple
T1479891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trent–Severn Waterway |
E30926
|
entity |
| Predicate | maximumVesselLength |
P29242
|
FINISHED |
| Object | 27.4 metres |
—
|
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: 27.4 metres | Statement: [Trent–Severn Waterway, maximumVesselLength, 27.4 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumVesselLength Context triple: [Trent–Severn Waterway, maximumVesselLength, 27.4 metres]
-
A.
maximumVesselType
Indicates the highest or largest class, size, or category of vessel that is allowed, applicable, or associated in a given context.
-
B.
maximumShipBeam
Indicates the greatest allowable or observed width of a ship across its widest point.
-
C.
naveLength
Indicates the length measurement of a building’s nave, typically from the entrance to the chancel or crossing.
-
D.
maximumTrunkDiameter
Indicates the largest thickness of a trunk measured across its widest point.
-
E.
baleenLength
Indicates the length of an organism’s baleen structures, typically measured as a physical dimension.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c674cc9c819088fc9146c7a7a914 |
completed | March 1, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69a4c484e52c81908948ff8c0a42751b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c57984088190b2c2d2d9cc2e5df9 |
completed | March 1, 2026, 11:02 p.m. |
Created at: March 1, 2026, 8:11 p.m.