Triple
T969596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of Cuba Broadcasting |
E20915
|
entity |
| Predicate | programmingFocus |
P22526
|
FINISHED |
| Object | news |
—
|
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: news | Statement: [Office of Cuba Broadcasting, programmingFocus, news]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programmingFocus Context triple: [Office of Cuba Broadcasting, programmingFocus, news]
-
A.
programFocus
Indicates that an educational or training program is primarily oriented around or concentrated on a particular subject, theme, or objective.
-
B.
programming
Indicates that an entity writes, develops, or modifies software or code, typically using a programming language to create or control computer programs.
-
C.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
D.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
E.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4497d688190b59c3a195e377080 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a579888190afb489ac9fe8391c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b385176081909e3e8c3f647c1fd4 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.