Triple
T36910427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujinomiya Route |
E912890
|
entity |
| Predicate | safetyFacilities |
P172749
|
FINISHED |
| Object | mountain huts |
—
|
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: mountain huts | Statement: [Fujinomiya Route, safetyFacilities, mountain huts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyFacilities Context triple: [Fujinomiya Route, safetyFacilities, mountain huts]
-
A.
hasSafetyInfrastructure
Indicates that appropriate safety-related structures, systems, or measures are present for the referenced entity or environment.
-
B.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
-
C.
hasPrecautionaryFacility
chosen
Indicates that an entity is equipped with or associated with a facility intended to provide precautionary or protective measures against potential risks or hazards.
-
D.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
E.
safetyCapacity
Indicates the maximum level or amount at which something can operate or be used while still remaining within safe limits.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:13 p.m.