Triple
T7327577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RJD |
E168912
|
entity |
| Predicate | hasVocationalPrograms |
P71155
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [RJD, hasVocationalPrograms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocationalPrograms Context triple: [RJD, hasVocationalPrograms, yes]
-
A.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
offersProfessionalPrograms
chosen
Indicates that an entity provides formal, career-oriented educational or training programs to others.
-
C.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
D.
hasOnlinePrograms
Indicates that an entity offers or provides programs, courses, or services that are available online.
-
E.
hasIndustryProgram
Indicates that an entity offers, participates in, or is associated with a structured program involving collaboration or engagement with industry organizations or sectors.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a755e88190a50126e2d1d6d4cb |
completed | March 27, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.