Triple
T1397724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia/Sydney |
E30704
|
entity |
| Predicate | timeZoneRegionType |
P27727
|
FINISHED |
| Object | city-based |
—
|
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: city-based | Statement: [Australia/Sydney, timeZoneRegionType, city-based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneRegionType Context triple: [Australia/Sydney, timeZoneRegionType, city-based]
-
A.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
-
B.
timeZoneName
Indicates the specific time zone designation (such as its standard name or label) associated with an entity.
-
C.
timeZoneDesignation
Indicates the specific time zone label or code assigned to an entity for representing its local time.
-
D.
relatedTimeZone
Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
-
E.
timeZoneDependence
Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c382b6588190833c39ac84fb6139 |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c13270d8819081d8ee1be34cabf5 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:59 p.m.