Triple
T21840617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neszmély |
E539241
|
entity |
| Predicate | hasWaterTransport |
P14751
|
FINISHED |
| Object | Danube navigation |
—
|
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: Danube navigation | Statement: [Neszmély, hasWaterTransport, Danube navigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterTransport Context triple: [Neszmély, hasWaterTransport, Danube navigation]
-
A.
transportsWaterTo
Indicates that one entity carries or conveys water from its location or source to another entity or destination.
-
B.
waterTransport
chosen
Indicates the movement or conveyance of something from one place to another via water-based means such as rivers, seas, or other aquatic routes.
-
C.
transportsWaterFrom
Indicates that one entity carries or conveys water from a specified source entity to another location or entity.
-
D.
hasFerryComponent
Indicates that something includes or is associated with a ferry-related part, feature, or segment within its structure or operation.
-
E.
hasWaterfrontAccessTo
Indicates that one entity is directly adjacent to and can physically access a particular body of water, such as a lake, river, or ocean.
- 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7ab71e081908e3d3293743e6409 |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:55 p.m.