Triple
T13366380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Norikura |
E318948
|
entity |
| Predicate | NorikuraSkylineStatus |
P109637
|
FINISHED |
| Object | one of the highest public roads in Japan |
—
|
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: one of the highest public roads in Japan | Statement: [Mount Norikura, NorikuraSkylineStatus, one of the highest public roads in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NorikuraSkylineStatus Context triple: [Mount Norikura, NorikuraSkylineStatus, one of the highest public roads in Japan]
-
A.
NorbulingkaStatus
Indicates the current condition, designation, or preservation state associated with Norbulingka.
-
B.
railStatus
Indicates the current operational condition or state of a rail-related entity (such as a track, line, or service) within the system.
-
C.
Scenic RailwayStatus
Indicates that an entity’s status or condition is specifically related to a scenic railway (e.g., whether it is active, inactive, under construction, or otherwise classified).
-
D.
cityCenterStatus
Indicates whether a location holds the status of being the central or main area of a city.
-
E.
landerStatus
Indicates the current operational or situational state of a lander in its mission lifecycle.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd652d48190a782fd1f57f34b6a |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:32 p.m.