Triple
T21485320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German federalism |
E530101
|
entity |
| Predicate | exclusiveLänderCompetenceArea |
P18508
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [German federalism, exclusiveLänderCompetenceArea, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exclusiveLänderCompetenceArea Context triple: [German federalism, exclusiveLänderCompetenceArea, education]
-
A.
countryRegionalOrganization
Indicates that a country is a member of, or affiliated with, a specific regional organization.
-
B.
competenceArea
chosen
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
C.
confluenceCountry
Indicates the country within whose territory a given confluence (meeting point of geographic coordinates or rivers) is located.
-
D.
rangeCountries
Indicates the set of countries over which something (such as a service, product, or data coverage) is available, applicable, or valid.
-
E.
sharesBilateralCooperationArea
Indicates that two entities engage in cooperative activities or initiatives within a specific, mutually agreed bilateral domain or sector.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea365a8481909635f614b23e751f |
completed | April 23, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:21 p.m.