Triple
T33513407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Entry/Exit System |
E858304
|
entity |
| Predicate | usesBiometrics |
P63130
|
FINISHED |
| Object | facial image |
—
|
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: facial image | Statement: [Entry/Exit System, usesBiometrics, facial image]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBiometrics Context triple: [Entry/Exit System, usesBiometrics, facial image]
-
A.
includesBiometrics
chosen
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
B.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
C.
hasFingerprintSensor
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
D.
supportsIdentity
Indicates that one entity upholds, validates, or reinforces the identity, self-concept, or role of another entity.
-
E.
hasFacialProfile
Indicates that an entity possesses a specific facial profile or configuration of facial features.
- 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_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:39 a.m.