Triple
T1647195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malaysia Time |
E35608
|
entity |
| Predicate | isUniformAcrossCountry |
P4880
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Malaysia Time, isUniformAcrossCountry, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUniformAcrossCountry Context triple: [Malaysia Time, isUniformAcrossCountry, true]
-
A.
usedUniformlyAcrossCountry
chosen
Indicates that something is applied or practiced in the same way throughout the entire country without regional variation.
-
B.
isUniqueWithinCountry
Indicates that an entity is the only one of its kind within the boundaries of a specific country.
-
C.
commonInCountry
Indicates that something occurs frequently or is widespread within a specified country.
-
D.
appliesToPersonNationality
Indicates that something is relevant or applicable specifically to a person’s nationality.
-
E.
typicalCountryIncluded
Indicates that a country is commonly or characteristically included within a given grouping, context, or set.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.