Triple
T5549569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gianni Letta |
E145491
|
entity |
| Predicate | mediaSectorActivity |
P41064
|
FINISHED |
| Object | print journalism |
—
|
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: print journalism | Statement: [Gianni Letta, mediaSectorActivity, print journalism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaSectorActivity Context triple: [Gianni Letta, mediaSectorActivity, print journalism]
-
A.
mediaFocus
Indicates that the primary attention, coverage, or emphasis of a media source is directed toward a particular entity or topic.
-
B.
mediaExposure
Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
-
C.
mediaActivity
chosen
Indicates an action or engagement involving the creation, use, sharing, or interaction with media content.
-
D.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
-
E.
mediaCovered
Indicates that one entity (such as a media outlet or source) has reported on, featured, or otherwise provided coverage of another entity or event.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe143ec8190bb67d2530c92a419 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.