Triple
T29924435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Media in Eritrea |
E760039
|
entity |
| Predicate | digitalMediaCharacteristic |
P107772
|
FINISHED |
| Object | limited internet penetration |
—
|
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: limited internet penetration | Statement: [Media in Eritrea, digitalMediaCharacteristic, limited internet penetration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: digitalMediaCharacteristic Context triple: [Media in Eritrea, digitalMediaCharacteristic, limited internet penetration]
-
A.
mediaCharacterization
Indicates how an entity is portrayed, described, or framed by media sources in terms of attributes, tone, or narrative.
-
B.
mediaFeature
chosen
Indicates a characteristic, capability, or attribute of a media item that distinguishes how it is presented, functions, or is experienced.
-
C.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
D.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
-
E.
visualTechnology
Indicates a relationship where one entity is a technology used to capture, process, display, or otherwise handle visual information for another entity or context.
- 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_69f224631674819080c8d089674f9f4f |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67795fdd4819088f3c7d0de598699 |
completed | May 2, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:15 p.m.