Triple
T21439361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 名谷キャンパス |
E528897
|
entity |
| Predicate | 主な学科 |
P104570
|
FINISHED |
| Object | 医学部保健学科 |
—
|
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: 医学部保健学科 | Statement: [名谷キャンパス, 主な学科, 医学部保健学科]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 主な学科 Context triple: [名谷キャンパス, 主な学科, 医学部保健学科]
-
A.
secondaryDiscipline
Indicates that an entity has an additional, subordinate field of study or area of specialization associated with it, distinct from its primary discipline.
-
B.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
C.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
D.
majorField
chosen
Indicates the primary academic discipline or field of study in which an entity (typically a person or program) specializes.
-
E.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b6feb2e48190ba5649f16a8bbbda |
completed | April 22, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 6:04 p.m.