Triple
T27300421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life University |
E688891
|
entity |
| Predicate | hasChiropracticCollege |
P72302
|
FINISHED |
| Object | Life University College of Chiropractic |
—
|
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: Life University College of Chiropractic | Statement: [Life University, hasChiropracticCollege, Life University College of Chiropractic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChiropracticCollege Context triple: [Life University, hasChiropracticCollege, Life University College of Chiropractic]
-
A.
hasMedicalCollege
Indicates that one entity possesses, hosts, or includes a medical college as part of its organization or structure.
-
B.
hasPharmacySchool
Indicates that an institution or entity includes, operates, or is affiliated with a school or program dedicated to the study and training of pharmacy.
-
C.
hasNursingSchool
Indicates that an entity possesses, hosts, or includes a nursing school as part of its organization or facilities.
-
D.
hasDentalSchool
Indicates that an institution or organization includes, operates, or is affiliated with a dental school.
-
E.
hasColleges
chosen
Indicates that an entity possesses, contains, or is associated with one or more colleges.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 27, 2026, 11:21 a.m.