Triple
T33670068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Champaign |
E862592
|
entity |
| Predicate | higherEducationInstitutionNearby |
P84383
|
FINISHED |
| Object | Parkland College |
—
|
NE NERFINISHED |
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: Parkland College | Statement: [City of Champaign, higherEducationInstitutionNearby, Parkland College]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherEducationInstitutionNearby Context triple: [City of Champaign, higherEducationInstitutionNearby, Parkland College]
-
A.
educationInstitutionNearby
Indicates that an educational institution is located close to a specified place or entity.
-
B.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
C.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
-
D.
hasNearbyInstitutionType
chosen
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
-
E.
schoolWithinUniversity
Indicates that a school (such as a college, faculty, or department) is an organizational unit that is part of and contained within a specific university.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 1, 2026, 1:42 a.m.