Triple
T577572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DCLK |
E13788
|
entity |
| Predicate | associatedCompanyRegionServed |
P82
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [DCLK, associatedCompanyRegionServed, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyRegionServed Context triple: [DCLK, associatedCompanyRegionServed, global]
-
A.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
B.
marketRegion
Indicates the geographic or demographic area in which a product, service, or entity is actively marketed or targeted.
-
C.
operatedInRegion
Indicates that an entity conducted operations or activities within a specified geographic region.
-
D.
areaServed
chosen
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
E.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b69fed88190b5558d4ebd5047a1 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c692288190b88f30299516b5ba |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.