Triple
T6910376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMM |
E159914
|
entity |
| Predicate | hasPrograms |
P6928
|
FINISHED |
| Object | educational programs |
—
|
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: educational programs | Statement: [SMM, hasPrograms, educational programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrograms Context triple: [SMM, hasPrograms, educational programs]
-
A.
hasProgramme
chosen
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
B.
hasPublicProgram
Indicates that an entity offers or participates in a program or initiative that is accessible to the general public.
-
C.
hasOnlinePrograms
Indicates that an entity offers or provides programs, courses, or services that are available online.
-
D.
hasMusicProgram
Indicates that an entity offers or is associated with an organized music-related program or curriculum.
-
E.
hasProgramCategory
Indicates that a program is classified under a specific category or type of program.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9c00e948190b103a2b2a2738bb1 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.