Triple
T1203825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université Laval |
E25841
|
entity |
| Predicate | offersAcademicPrograms |
P20124
|
FINISHED |
| Object | undergraduate 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: undergraduate programs | Statement: [Université Laval, offersAcademicPrograms, undergraduate programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersAcademicPrograms Context triple: [Université Laval, offersAcademicPrograms, undergraduate programs]
-
A.
hasUndergraduatePrograms
chosen
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
B.
offersInternationalPrograms
Indicates that an institution or organization provides programs or courses available to participants from other countries or across national borders.
-
C.
offersFellowshipPrograms
Indicates that an entity provides or makes available fellowship programs to individuals or other entities.
-
D.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
E.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbf94188190991f63a84cc76b8a |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.