Triple
T25588035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myki Pass |
E641439
|
entity |
| Predicate | typicalZones |
P194059
|
FINISHED |
| Object | Zone 1 |
—
|
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: Zone 1 | Statement: [Myki Pass, typicalZones, Zone 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalZones Context triple: [Myki Pass, typicalZones, Zone 1]
-
A.
otherZones
Indicates that an entity is associated with or belongs to zones that are distinct from a primary or reference zone.
-
B.
typicalRegionType
Indicates that a region is of a characteristic or commonly occurring type for a given context or entity.
-
C.
zoneType
Indicates the classification or category of a zone that specifies its type or functional designation.
-
D.
characteristicOfZone
Indicates that a particular characteristic, feature, or property is associated with and defines a specific zone or area.
-
E.
typicalDistricts
Indicates that certain districts are characteristic or representative examples of a larger region, category, or entity.
- F. None of above. chosen
Provenance (4 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
| PDg | Predicate description generation | batch_69fd5f2903a48190ac4b718bff99c6cf |
completed | May 8, 2026, 3:57 a.m. |
Created at: April 21, 2026, 4:18 p.m.