Triple
T293349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep South |
E6040
|
entity |
| Predicate | culturalInfluenceFrom |
P2008
|
FINISHED |
| Object | African American 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: African American culture | Statement: [Deep South, culturalInfluenceFrom, African American culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalInfluenceFrom Context triple: [Deep South, culturalInfluenceFrom, African American culture]
-
A.
hasCulturalImpact
chosen
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
B.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
C.
hasHistoricalWritingInfluenceFrom
Indicates that one entity’s historical writing style, content, or traditions are influenced by those of another entity.
-
D.
hasCulturalSignificance
Indicates that something holds notable meaning, value, or importance within a particular culture or cultural context.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e934b4408190b53a17f57a02df65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.