Triple
T32348659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Africa/Casablanca |
E826533
|
entity |
| Predicate | timeZoneAbbreviationTypical |
P76954
|
FINISHED |
| Object | WET |
—
|
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: WET | Statement: [Africa/Casablanca, timeZoneAbbreviationTypical, WET]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneAbbreviationTypical Context triple: [Africa/Casablanca, timeZoneAbbreviationTypical, WET]
-
A.
DSTAbbreviation
Indicates that one entity is the standard abbreviated form used to represent another entity related to daylight saving time.
-
B.
zoneAbbreviation
chosen
Indicates that one entity is the abbreviated or short-form representation of a particular zone associated with another entity.
-
C.
includesTimeZoneAbbreviation
Indicates that something explicitly contains or specifies a time zone abbreviation as part of its representation or data.
-
D.
timeZoneDesignation
Indicates the specific time zone label or code assigned to an entity for representing its local time.
-
E.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6be5439b08190a297764d3384a6d1 |
completed | May 3, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:49 a.m.