Triple
T7927781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DIY Network |
E184109
|
entity |
| Predicate | typicalProgrammingIncludes |
P10191
|
FINISHED |
| Object | instructional renovation shows |
—
|
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: instructional renovation shows | Statement: [DIY Network, typicalProgrammingIncludes, instructional renovation shows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalProgrammingIncludes Context triple: [DIY Network, typicalProgrammingIncludes, instructional renovation shows]
-
A.
programmingIncludes
chosen
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
-
B.
typicalProgrammingSource
Indicates that one entity is a common or standard source from which the other entity obtains programming content or code.
-
C.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
D.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
E.
notableProgrammingCategory
Indicates that an entity is recognized as belonging to a significant or distinguished category within the domain of programming.
- 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_69ca828fe7bc819090f52c88dcd72183 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aafdb5c8190b7f2ce5349305f78 |
completed | March 31, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69cae9316e98819080be7bf1a6ff92f1 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:07 p.m.