Triple
T1440385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Griggs v. Duke Power Co. |
E31055
|
entity |
| Predicate | impactOnGroup |
P10927
|
FINISHED |
| Object | African American workers |
—
|
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 workers | Statement: [Griggs v. Duke Power Co., impactOnGroup, African American workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnGroup Context triple: [Griggs v. Duke Power Co., impactOnGroup, African American workers]
-
A.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
B.
affectedEthnicGroup
chosen
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
-
C.
impactOnPerformance
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
-
D.
coveredGroup
Indicates that one group or set is included within, or has its members protected or accounted for by, another group or arrangement.
-
E.
socialGroupInvolved
Indicates that a particular social group participates in, is affected by, or is otherwise involved in the specified event or situation.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.