Triple
T6546343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBS Films |
E151016
|
entity |
| Predicate | mediaSector |
P72306
|
FINISHED |
| Object | film production |
—
|
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: film production | Statement: [CBS Films, mediaSector, film production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaSector Context triple: [CBS Films, mediaSector, film production]
-
A.
mediaFocus
Indicates that the primary attention, coverage, or emphasis of a media source is directed toward a particular entity or topic.
-
B.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
-
C.
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.
-
D.
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.
-
E.
mediaEnvironment
Indicates the surrounding media or contextual setting in which an entity exists, operates, or is presented.
- F. None of above. chosen
Provenance (4 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6ce0538f48190abf3160681901c17 |
completed | March 27, 2026, 6:35 p.m. |
Created at: March 27, 2026, 1:50 p.m.