Triple
T37661159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsung Galaxy Note 4 |
E937719
|
entity |
| Predicate | supportsFingerprintSensor |
—
|
GENERATED |
| Object | yes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFingerprintSensor Context triple: [Samsung Galaxy Note 4, supportsFingerprintSensor, yes]
-
A.
hasFingerprintSensor
chosen
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
B.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
C.
fingerprintSHA256
Indicates that one entity is the SHA-256 fingerprint (cryptographic hash identifier) of another entity.
-
D.
includesBiometrics
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
E.
fingerprintSHA1
Indicates that one entity is the SHA-1 fingerprint (cryptographic hash identifier) of another entity.
- F. None of above.
Provenance (1 batch)
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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:18 p.m.