Triple
T11029988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand passports |
E260730
|
entity |
| Predicate | biometric |
P63130
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [New Zealand passports, biometric, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: biometric Context triple: [New Zealand passports, biometric, yes]
-
A.
includesBiometrics
chosen
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
B.
signatureFeature
Indicates that one entity is a defining or characteristic feature that distinctly identifies or typifies another entity.
-
C.
biologicalCharacteristic
Indicates that one entity possesses or exhibits a particular biological trait, feature, or property in relation to another.
-
D.
recognizesIndividual
Indicates that one entity identifies or acknowledges the identity or presence of a specific individual.
-
E.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d2feb881909a5684721e8b0d9c |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:25 p.m.