Triple
T8199290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université de Hearst |
E191525
|
entity |
| Predicate | academicProgramsMedium |
P81455
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Université de Hearst, academicProgramsMedium, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicProgramsMedium Context triple: [Université de Hearst, academicProgramsMedium, French]
-
A.
hasAcademicProgramsWith
Indicates that two institutions or entities offer or participate in the same or jointly organized academic programs.
-
B.
postgraduatePrograms
Indicates that an institution offers or is associated with academic programs pursued after completion of an undergraduate degree.
-
C.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
D.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
E.
offersProfessionalPrograms
Indicates that an entity provides formal, career-oriented educational or training programs to others.
- 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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df426cc81908b676d3d6852e29f |
completed | March 31, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69cb36aac86081909b83636e352e0ced |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb46635424819085d086972b264280 |
completed | March 31, 2026, 3:58 a.m. |
Created at: March 30, 2026, 5:42 p.m.