Triple
T16744615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Yōtei |
E406918
|
entity |
| Predicate | hasAscentRoute |
P2405
|
FINISHED |
| Object |
Kimobetsu course
Kimobetsu course is a popular hiking and climbing route used to ascend Mount Yōtei in Hokkaido, Japan.
|
E1232740
|
NE FINISHED |
How this triple was built (4 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: Kimobetsu course | Statement: [Mount Yōtei, hasAscentRoute, Kimobetsu course]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimobetsu course Context triple: [Mount Yōtei, hasAscentRoute, Kimobetsu course]
-
A.
Shirakumobashi course
Shirakumobashi course is a hiking trail on Mount Tsukuba in Japan, known for its scenic forest paths and access to the mountain’s twin peaks.
-
B.
Miyukigahara course
Miyukigahara course is a popular hiking trail on Mount Tsukuba in Japan, known for its accessible route and scenic views.
-
C.
Daigakuryō
Daigakuryō was the imperial university of ancient Japan, serving as the central state institution for educating aristocratic bureaucrats in Confucian classics and government administration.
-
D.
Kanagawa-juku
Kanagawa-juku was a post station along Japan’s historic Tōkaidō road, serving as a key rest and relay point for travelers during the Edo period.
-
E.
Kindai
Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kimobetsu course Triple: [Mount Yōtei, hasAscentRoute, Kimobetsu course]
Generated description
Kimobetsu course is a popular hiking and climbing route used to ascend Mount Yōtei in Hokkaido, Japan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kimobetsu course Target entity description: Kimobetsu course is a popular hiking and climbing route used to ascend Mount Yōtei in Hokkaido, Japan.
-
A.
Shirakumobashi course
Shirakumobashi course is a hiking trail on Mount Tsukuba in Japan, known for its scenic forest paths and access to the mountain’s twin peaks.
-
B.
Miyukigahara course
Miyukigahara course is a popular hiking trail on Mount Tsukuba in Japan, known for its accessible route and scenic views.
-
C.
Daigakuryō
Daigakuryō was the imperial university of ancient Japan, serving as the central state institution for educating aristocratic bureaucrats in Confucian classics and government administration.
-
D.
Kanagawa-juku
Kanagawa-juku was a post station along Japan’s historic Tōkaidō road, serving as a key rest and relay point for travelers during the Edo period.
-
E.
Kindai
Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
- F. None of above. chosen
Provenance (5 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa210ef88190be74bd60d7144953 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a51e69c08190a5bff74823df430c |
completed | May 10, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a00a782502c819086c07dbcfc1b46eb |
completed | May 10, 2026, 3:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a7e3725c81909afbf1abb4eb317b |
completed | May 10, 2026, 3:44 p.m. |
Created at: April 10, 2026, 5:21 a.m.