Triple
T1835682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Templeman |
E41060
|
entity |
| Predicate | mediaAppearanceFrequency |
P5080
|
FINISHED |
| Object | rare |
—
|
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: rare | Statement: [Joan Templeman, mediaAppearanceFrequency, rare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaAppearanceFrequency Context triple: [Joan Templeman, mediaAppearanceFrequency, rare]
-
A.
mediaPresence
Indicates the extent to which something is visible, represented, or covered within various media channels or platforms.
-
B.
mediaProfile
Indicates a relationship where a media-related profile or account is associated with an entity, typically representing its presence or identity in media contexts.
-
C.
mediaCharacterization
Indicates how an entity is portrayed, described, or framed by media sources in terms of attributes, tone, or narrative.
-
D.
mediaAttentionLevel
chosen
Indicates the degree or intensity of attention or coverage that media outlets give to a particular subject or entity.
-
E.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.