Triple
T21879209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Wizard of the Ku Klux Klan |
E540232
|
entity |
| Predicate | hasNegativeImpactOn |
P125238
|
FINISHED |
| Object | civil rights |
—
|
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: civil rights | Statement: [Grand Wizard of the Ku Klux Klan, hasNegativeImpactOn, civil rights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNegativeImpactOn Context triple: [Grand Wizard of the Ku Klux Klan, hasNegativeImpactOn, civil rights]
-
A.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
canImpact
chosen
Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
-
C.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
-
D.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
E.
hasVisualImpact
Indicates that one entity affects or influences the visual appearance or aesthetic perception of another.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118e42c108190b6308016655c429e |
completed | April 28, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:03 p.m.