Triple
T22558098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Netherlands and Germany |
E557738
|
entity |
| Predicate | haveSharedInstitutions |
P38884
|
FINISHED |
| Object | Benelux–Germany cooperation formats |
—
|
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: Benelux–Germany cooperation formats | Statement: [Netherlands and Germany, haveSharedInstitutions, Benelux–Germany cooperation formats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveSharedInstitutions Context triple: [Netherlands and Germany, haveSharedInstitutions, Benelux–Germany cooperation formats]
-
A.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
B.
commonInstitution
chosen
Indicates that two or more entities share affiliation with the same institution (such as an organization, school, or company).
-
C.
hasCommonOrganizations
Indicates that two entities share one or more organizations in which they are both involved or affiliated.
-
D.
sharesInstitution
Indicates that two entities are affiliated with or belong to the same institution.
-
E.
hadDistinctInstitution
Indicates that the entities were associated with different institutions, rather than sharing the same one.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7b06e08190b3ca82a783965942 |
completed | April 29, 2026, 1:31 a.m. |
| PD | Predicate disambiguation | batch_69e898cb3fb48190add6ab24a2df5822 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:52 p.m.