Triple
T23333760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euroregion Elbe/Labe |
E591516
|
entity |
| Predicate | hasCrossBorderCenter |
P151901
|
FINISHED |
| Object | Děčín |
—
|
NE NERFINISHED |
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: Děčín | Statement: [Euroregion Elbe/Labe, hasCrossBorderCenter, Děčín]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossBorderCenter Context triple: [Euroregion Elbe/Labe, hasCrossBorderCenter, Děčín]
-
A.
hasCrossBorderArea
Indicates that an entity is associated with or spans a geographic area that extends across national or jurisdictional borders.
-
B.
isCrossBorder
Indicates that the relationship or action involves entities located in or spanning across different national or jurisdictional boundaries.
-
C.
hasCrossBorderManagement
Indicates that an entity exercises management or control over operations, assets, or activities that extend across national borders.
-
D.
hasCrossBorderInteraction
Indicates that there is an interaction, activity, or relationship occurring between entities located in different countries or jurisdictions.
-
E.
hasCrossBorderTrade
Indicates that there is trade or commercial exchange occurring between entities located in different countries or jurisdictions.
- 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197efd98c819083635a2b8440f3eb |
completed | April 29, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
| PDg | Predicate description generation | batch_69f01d88b4ec8190a2a17a88e0eda178 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 17, 2026, 5:16 p.m.