Triple
T21439510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 法学部 |
E528900
|
entity |
| Predicate | 類似学部 |
P62590
|
FINISHED |
| Object | 政治経済学部 |
—
|
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: 政治経済学部 | Statement: [法学部, 類似学部, 政治経済学部]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 類似学部 Context triple: [法学部, 類似学部, 政治経済学部]
-
A.
isUndergraduateCounterpartOf
Indicates that one academic program, course, or role is the undergraduate-level counterpart of another at a higher (e.g., graduate) level.
-
B.
similarInstitution
chosen
Indicates that two institutions share notable similarities, such as in type, function, structure, or role.
-
C.
universityUnitType
Indicates the specific category or type of organizational unit within a university (such as department, faculty, school, or institute) that an entity belongs to.
-
D.
university2
Indicates a relationship where an entity is a university associated with, attended by, or otherwise linked to another entity.
-
E.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
- 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, 6:05 p.m.