Triple
T2316176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Starkenborghkanaal |
E51068
|
entity |
| Predicate | hasMaximumVesselClass |
P2429
|
FINISHED |
| Object | CEMT class Va |
—
|
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: CEMT class Va | Statement: [Van Starkenborghkanaal, hasMaximumVesselClass, CEMT class Va]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumVesselClass Context triple: [Van Starkenborghkanaal, hasMaximumVesselClass, CEMT class Va]
-
A.
maximumVesselType
chosen
Indicates the highest or largest class, size, or category of vessel that is allowed, applicable, or associated in a given context.
-
B.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
C.
maximumVesselLength
Indicates the greatest allowable or observed length of a vessel in a given context or constraint.
-
D.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
E.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.