Triple
T26436589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacMurray College |
E664965
|
entity |
| Predicate | campusCharacter |
P117450
|
FINISHED |
| Object | close-knit campus community |
—
|
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: close-knit campus community | Statement: [MacMurray College, campusCharacter, close-knit campus community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusCharacter Context triple: [MacMurray College, campusCharacter, close-knit campus community]
-
A.
hasCampusCharacter
chosen
Indicates that an institution possesses a particular overall campus atmosphere, style, or defining quality.
-
B.
campusLandmark
Indicates that something serves as a notable or recognizable landmark located on or associated with a campus.
-
C.
hasCampusTownCharacter
Indicates that a place exhibits qualities or atmosphere typically associated with a college or university town.
-
D.
universityMascot
Indicates that one entity serves as the official mascot representing a particular university.
-
E.
studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
- 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_69ee883c851881909e2ab04efbb3c5fe |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f61217c7dc8190bd76149fba4fce97 |
completed | May 2, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 11:54 p.m.