Triple
T38081502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Red Cross nursing colleges |
E950863
|
entity |
| Predicate | offersTrainingComponent |
P140901
|
FINISHED |
| Object | clinical practicum |
—
|
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: clinical practicum | Statement: [Japanese Red Cross nursing colleges, offersTrainingComponent, clinical practicum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersTrainingComponent Context triple: [Japanese Red Cross nursing colleges, offersTrainingComponent, clinical practicum]
-
A.
offersTrainingLevel
Indicates that one entity provides or makes available a specific level or tier of training to another entity.
-
B.
offersEducationIn
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
C.
offersEducationTo
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
D.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
-
E.
offersProgramComponent
chosen
Indicates that an entity provides or makes available a specific program component as part of its offerings.
- 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_69f76f03a3608190a73fd6df87c792a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69febce5877c8190a5e000ef5331ec88 |
completed | May 9, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69febad1cd588190abc7686bcb39a371 |
completed | May 9, 2026, 4:40 a.m. |
Created at: May 3, 2026, 4:21 p.m.