Triple
T19907323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zone System |
E478452
|
entity |
| Predicate | zoneCount |
P137773
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Zone System, zoneCount, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoneCount Context triple: [Zone System, zoneCount, 11]
-
A.
zoneType
Indicates the classification or category of a zone that specifies its type or functional designation.
-
B.
hasNumberOfNationalTimeZones
Indicates the quantity of distinct official time zones that a nation or country uses within its territory.
-
C.
zoneConcept
Indicates that one entity is associated with, defined by, or operates within a particular zone or conceptual area specified by another entity.
-
D.
zoneNumberRange
Indicates that there is an associated range of zone numbers, typically specifying the minimum and maximum zone identifiers applicable in a given context.
-
E.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6598cc5108190bca2a47c9f8ef70f |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.