Triple
T10657854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnesota and Wisconsin |
E251140
|
entity |
| Predicate | shareHigherEducationFeature |
P95193
|
FINISHED |
| Object | large public university systems |
—
|
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: large public university systems | Statement: [Minnesota and Wisconsin, shareHigherEducationFeature, large public university systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareHigherEducationFeature Context triple: [Minnesota and Wisconsin, shareHigherEducationFeature, large public university systems]
-
A.
sharesInstitution
Indicates that two entities are affiliated with or belong to the same institution.
-
B.
sharesCampusWith
Indicates that two entities are located on or use the same campus or campus facilities.
-
C.
sharesHighSchool
Indicates that two entities attended the same high school.
-
D.
sharesCurriculumWith
Indicates that two educational programs or courses use the same or substantially overlapping curriculum content.
-
E.
sharesFacultyWith
Indicates that two academic institutions or departments have at least one faculty member in common or on staff at both.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e01643a88190abc7c16fd0f85e53 |
completed | April 8, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69d6dd8753108190b799ffa0c760526e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:07 p.m.