Triple
T4855644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France and Switzerland |
E108530
|
entity |
| Predicate | haveCulturalTies |
P38730
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [France and Switzerland, haveCulturalTies, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveCulturalTies Context triple: [France and Switzerland, haveCulturalTies, yes]
-
A.
hasCulturalRelation
chosen
Indicates a relationship in which entities are connected through shared, influencing, or interacting cultural practices, values, traditions, or expressions.
-
B.
hasAssociatedCulture
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
C.
hasStrongCulturalIdentity
Indicates that an entity possesses a well-defined, deeply rooted, and strongly maintained sense of belonging to a particular culture or cultural tradition.
-
D.
culturallySimilarTo
Indicates that two entities share comparable cultural characteristics, practices, or values.
-
E.
hasCulturalLegacyIn
Indicates that an entity has left a lasting cultural influence, impact, or heritage within a particular place, community, or cultural context.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.