Triple
T12880639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian passports |
E308082
|
entity |
| Predicate | firstBiometricVersionIntroduced |
P20170
|
FINISHED |
| Object | mid-2000s |
—
|
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: mid-2000s | Statement: [Australian passports, firstBiometricVersionIntroduced, mid-2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstBiometricVersionIntroduced Context triple: [Australian passports, firstBiometricVersionIntroduced, mid-2000s]
-
A.
includesBiometrics
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
B.
hasFingerprintSensor
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
C.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
D.
firstUsedOn
chosen
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
-
E.
firstPresentedFor
Indicates that one entity was initially introduced, submitted, or shown to another entity at a particular time or context.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.