Triple
T11246034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 青葉山キャンパス |
E266206
|
entity |
| Predicate | 立地環境 |
P80113
|
FINISHED |
| Object | 丘陵地 |
—
|
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: 丘陵地 | Statement: [青葉山キャンパス, 立地環境, 丘陵地]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 立地環境 Context triple: [青葉山キャンパス, 立地環境, 丘陵地]
-
A.
立地特性
chosen
Indicates the characteristics or qualities of a location that define its situational conditions or advantages in relation to its surroundings.
-
B.
agriculturalEnvironment
Indicates that something exists in, is associated with, or is influenced by an agricultural or farming-related environment.
-
C.
محیط زیست
Indicates a relationship involving the natural environment, such as the impact of actions on ecological systems, resources, and living conditions.
-
D.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
E.
environmentalCondition
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91c045c81908a9024a8aee32f4d |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.