Triple
T1976024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 United States census |
E42912
|
entity |
| Predicate | dataProtectionMethod |
P15826
|
FINISHED |
| Object | differential privacy |
—
|
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: differential privacy | Statement: [2020 United States census, dataProtectionMethod, differential privacy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataProtectionMethod Context triple: [2020 United States census, dataProtectionMethod, differential privacy]
-
A.
protectionType
chosen
Indicates the kind or method of protection that is applied to or associated with an entity.
-
B.
dataPolicy
Indicates that one entity defines or governs how data related to another entity is collected, used, stored, or shared.
-
C.
protectionLevel
Indicates the degree or extent to which something is safeguarded against harm, risk, or unauthorized access.
-
D.
protectedEntity
Indicates that one entity is safeguarded or defended by another entity or mechanism.
-
E.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f835108190b0709ccf3a487a96 |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.