Triple
T3134157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam–Rhine Canal |
E65486
|
entity |
| Predicate | maxVesselTonnage |
P45572
|
FINISHED |
| Object | approximately 4000 tonnes |
—
|
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 4000 tonnes | Statement: [Amsterdam–Rhine Canal, maxVesselTonnage, approximately 4000 tonnes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxVesselTonnage Context triple: [Amsterdam–Rhine Canal, maxVesselTonnage, approximately 4000 tonnes]
-
A.
maximumVesselType
Indicates the highest or largest class, size, or category of vessel that is allowed, applicable, or associated in a given context.
-
B.
maximumVesselLength
Indicates the greatest allowable or observed length of a vessel in a given context or constraint.
-
C.
maximumVesselDraft
Indicates the greatest depth a vessel can safely extend below the waterline, typically limiting where it can navigate or dock.
-
D.
maximumShipBeam
Indicates the greatest allowable or observed width of a ship across its widest point.
-
E.
maximumVesselAirDraft
Indicates the greatest vertical distance from the waterline to the highest point of a vessel that is allowed or applicable in a given context.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada562540081908627950dd0b56a1e |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:05 p.m.