Triple
T478282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parkland College |
E9108
|
entity |
| Predicate | offersStudentService |
P8172
|
FINISHED |
| Object | academic advising |
—
|
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: academic advising | Statement: [Parkland College, offersStudentService, academic advising]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersStudentService Context triple: [Parkland College, offersStudentService, academic advising]
-
A.
offersServiceTo
chosen
Indicates that one entity provides or makes a service available for the benefit or use of another entity.
-
B.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
C.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
D.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
-
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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03f3fbc81909af6e4496d5e6c2a |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf017548190ae38ff3314a1ffa3 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.