Triple
T12173067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle Sinclair |
E290018
|
entity |
| Predicate | hasMediaAttention |
P5080
|
FINISHED |
| Object | national media in the United States |
—
|
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: national media in the United States | Statement: [Michelle Sinclair, hasMediaAttention, national media in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaAttention Context triple: [Michelle Sinclair, hasMediaAttention, national media in the United States]
-
A.
hasMediaCoverageSince
Indicates that an entity has had media coverage starting from a specified point in time and continuing from then onward.
-
B.
hasMediaCoverageLevel
Indicates the degree or extent to which something is covered or reported on by media outlets.
-
C.
mediaAttentionLevel
chosen
Indicates the degree or intensity of attention or coverage that media outlets give to a particular subject or entity.
-
D.
hasStatusInMedia
Indicates that an entity is portrayed with a particular status or condition within a specific media work or context.
-
E.
mediaCoverageAs
Indicates that one entity provides or receives media coverage in the role, capacity, or format specified by another entity.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.