Triple
T2357391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Netherlands–United States relations |
E47587
|
entity |
| Predicate | hasCulturalRelation |
P38730
|
FINISHED |
| Object | academic exchanges |
—
|
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: academic exchanges | Statement: [Netherlands–United States relations, hasCulturalRelation, academic exchanges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalRelation Context triple: [Netherlands–United States relations, hasCulturalRelation, academic exchanges]
-
A.
hasAssociatedCulture
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
B.
culturallySimilarTo
Indicates that two entities share comparable cultural characteristics, practices, or values.
-
C.
hasCulturalConcept
Indicates that an entity embodies, includes, or is associated with a particular cultural idea, value, practice, or construct.
-
D.
isCulturalLanguageOf
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
E.
hasCulturalFeature
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcb7ebb708190ba7edffee3c45d8b |
completed | March 7, 2026, 6:53 a.m. |
Created at: March 4, 2026, 7:54 p.m.