Triple
T20458893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star+ |
E501866
|
entity |
| Predicate | offersOriginalProgramming |
P140175
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Star+, offersOriginalProgramming, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersOriginalProgramming Context triple: [Star+, offersOriginalProgramming, true]
-
A.
offersSyndicatedProgramming
Indicates that one entity provides syndicated programming content for distribution or broadcast by another entity.
-
B.
hasOriginalProgrammingType
Indicates that an entity has a specific type or category of original programming associated with it.
-
C.
hasOriginalProgrammingBrand
Indicates that an entity is associated with or produced under a particular original programming brand or label.
-
D.
sponsoredTelevisionSeries
Indicates that an entity provides financial or promotional support for a particular television series.
-
E.
offersProgramFormat
Indicates that an entity provides or makes available a specific type or format of program.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a4652c8190acf79fa2e285e436 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:33 a.m.