Triple
T7296037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poland–Germany relations |
E164522
|
entity |
| Predicate | hasCooperationArea |
P26572
|
FINISHED |
| Object | cross-border regional cooperation |
—
|
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: cross-border regional cooperation | Statement: [Poland–Germany relations, hasCooperationArea, cross-border regional cooperation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCooperationArea Context triple: [Poland–Germany relations, hasCooperationArea, cross-border regional cooperation]
-
A.
definesCooperationWith
Indicates that one entity formally specifies or establishes the terms, scope, or nature of cooperative interaction with another entity.
-
B.
collaborationArea
chosen
Indicates the domain, topic, or field in which two or more entities work together or collaborate.
-
C.
collaborationRegion
Indicates the geographic or administrative area within which the collaboration between entities takes place or is defined.
-
D.
hasCooperative
Indicates that one entity participates in a cooperative relationship or partnership with another entity.
-
E.
cooperationType
Indicates the specific kind or form of cooperative relationship that exists between the related entities.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8d0c6c8190b32cd08b9a5d96cc |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.