Triple
T4893345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOA Africa |
E109614
|
entity |
| Predicate | coverageTopic |
P26448
|
FINISHED |
| Object | African politics |
—
|
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: African politics | Statement: [VOA Africa, coverageTopic, African politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverageTopic Context triple: [VOA Africa, coverageTopic, African politics]
-
A.
coverageScope
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
B.
featuresTopic
chosen
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
C.
legalTopicCoverage
Indicates that one entity (such as a document, service, or resource) addresses, discusses, or is relevant to a particular legal topic or area of law.
-
D.
coversPolicyArea
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
-
E.
governedTopic
Indicates that a governing entity exercises authority, control, or regulatory oversight over a particular topic, issue, or domain.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.