Triple
T26771044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B2 Entertainment |
E675077
|
entity |
| Predicate | typeOfProgrammingProduced |
P179073
|
FINISHED |
| Object | reality programming |
—
|
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: reality programming | Statement: [B2 Entertainment, typeOfProgrammingProduced, reality programming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfProgrammingProduced Context triple: [B2 Entertainment, typeOfProgrammingProduced, reality programming]
-
A.
genreOfProgramming
chosen
Indicates that one entity is a programming genre or paradigm to which the other entity (a programming language, framework, or codebase) belongs.
-
B.
programLanguage
Indicates that an entity is implemented, written, or expressed using a particular programming language.
-
C.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
D.
languageOfProgramming
Indicates that one entity is a programming language used to implement, develop, or script the other entity.
-
E.
programType
Indicates the category or kind of program to which an entity belongs or with which it is associated.
- 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_69eecda85298819097ee1c38a3d772e7 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 27, 2026, 4:02 a.m.