Triple
T9982833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English people |
E196493
|
entity |
| Predicate | cultureInfluenceOn |
P2008
|
FINISHED |
| Object | global culture |
—
|
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: global culture | Statement: [English people, cultureInfluenceOn, global culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cultureInfluenceOn Context triple: [English people, cultureInfluenceOn, global culture]
-
A.
hasCulturalImpact
chosen
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
B.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
C.
heritageInfluence
Indicates how one entity’s cultural, historical, or ancestral background affects or shapes another entity’s characteristics, behavior, or development.
-
D.
influenceOnArt
Indicates that one entity has affected, shaped, or inspired the artistic style, content, or development of another.
-
E.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bca41081909c04fb77603403b9 |
completed | April 2, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:49 p.m.