Triple
T27849386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 総合文化研究科 |
E703907
|
entity |
| Predicate | 分野横断性 |
P18353
|
FINISHED |
| Object | 高い |
—
|
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: 高い | Statement: [総合文化研究科, 分野横断性, 高い]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 分野横断性 Context triple: [総合文化研究科, 分野横断性, 高い]
-
A.
crossCut
Indicates that one entity intersects or passes through another, typically cutting across it from one side to the other.
-
B.
isMultidisciplinary
chosen
Indicates that something involves or integrates multiple distinct academic or professional disciplines in its approach or composition.
-
C.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
-
D.
disciplinaryFocus
Indicates the primary academic or professional field, subject area, or discipline that something is centered on or concerned with.
-
E.
crossedBoundary
Indicates that an entity has moved from one defined area, region, or limit into another, thereby passing across a specified boundary.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f639040e748190a283658f38d24ef7 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 6:09 p.m.