Triple
T22237026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EU Strategy for the Danube Region |
E549617
|
entity |
| Predicate | hasPriorityArea |
P25176
|
FINISHED |
| Object | inland waterways |
—
|
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: inland waterways | Statement: [EU Strategy for the Danube Region, hasPriorityArea, inland waterways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPriorityArea Context triple: [EU Strategy for the Danube Region, hasPriorityArea, inland waterways]
-
A.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
B.
hasSectoralPriority
Indicates that something is designated as having priority or special importance within a particular sector or industry.
-
C.
hasAreaOfInterest
chosen
Indicates that an entity possesses or is associated with a particular area of interest or focus.
-
D.
hasImpactArea
Indicates that an entity affects, influences, or has consequences within a specific area, domain, or scope.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf7b1d8819091087dcfdb2e967c |
completed | April 28, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:38 p.m.