Triple
T40573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time |
E801
|
entity |
| Predicate | circulationArea |
P82
|
FINISHED |
| Object | worldwide |
—
|
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: worldwide | Statement: [Time, circulationArea, worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circulationArea Context triple: [Time, circulationArea, worldwide]
-
A.
circulation
Indicates the movement or flow of something (such as information, materials, or currency) through a system, network, or among entities.
-
B.
areaServed
chosen
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
C.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
D.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
E.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b80f4a8819090d2bffe29824b90 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ab74c548190a54872e15c8394c3 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.