Triple
T11845604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finlandia University |
E281765
|
entity |
| Predicate | hadStudentBodyCharacteristic |
P5246
|
FINISHED |
| Object | close-knit 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 community | Statement: [Finlandia University, hadStudentBodyCharacteristic, close-knit community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadStudentBodyCharacteristic Context triple: [Finlandia University, hadStudentBodyCharacteristic, close-knit community]
-
A.
hasStudentBodyFrom
Indicates that an educational institution draws or enrolls its student body from a specified geographic area, group, or source.
-
B.
hasStudentBodyType
chosen
Indicates that an educational institution possesses a student body characterized by a particular type or classification.
-
C.
hasCourseCharacteristic
Indicates that a course possesses or is associated with a particular characteristic, feature, or attribute.
-
D.
subjectHasCharacteristic
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
-
E.
representsStudentBody
Indicates that one entity serves as the official representative or governing body for the students of another entity (such as a school or institution).
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65b5ff08190bb58361f6a6acdca |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.