Triple
T21800491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 横浜たまプラーザキャンパス |
E538225
|
entity |
| Predicate | hasFacilityQuality |
P145691
|
FINISHED |
| Object | 近代的な設備が整備されている |
—
|
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: 近代的な設備が整備されている | Statement: [横浜たまプラーザキャンパス, hasFacilityQuality, 近代的な設備が整備されている]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacilityQuality Context triple: [横浜たまプラーザキャンパス, hasFacilityQuality, 近代的な設備が整備されている]
-
A.
hasFacilityLevel
Indicates the degree or tier of capability, service, or infrastructure that a particular facility possesses.
-
B.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
D.
hasFacilityLocation
Indicates that an entity possesses or is associated with a facility situated at a specific location.
-
E.
hasFacilityFunction
Indicates that a facility performs, supports, or is designated for a particular function or operational role.
- F. None of above. chosen
Provenance (4 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077fede848190b8fe07941d6573d9 |
completed | April 28, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69e6c3a2898881909748935cf92f898c |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 6:53 p.m.