Triple
T18042366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biometrics Commissioner |
E431680
|
entity |
| Predicate | typeOfBiometricsCovered |
P63130
|
FINISHED |
| Object | fingerprints |
—
|
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: fingerprints | Statement: [Biometrics Commissioner, typeOfBiometricsCovered, fingerprints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBiometricsCovered Context triple: [Biometrics Commissioner, typeOfBiometricsCovered, fingerprints]
-
A.
includesBiometrics
chosen
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
B.
securityTypeCoverage
Indicates the type or category of security that is covered or included under a given coverage or policy.
-
C.
typeOfIdentity
Indicates the specific category or nature of identity that characterizes or defines an entity within a given context.
-
D.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
E.
typeOfDiscriminationCovered
Indicates that a particular kind or category of discriminatory behavior is included within the scope of protections, rules, or analysis.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bfef454c8190ad3787502f2bdd34 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.