Triple
T6868710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokushima |
E158482
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Mount Bizan
Mount Bizan is a small, scenic mountain in Tokushima, Japan, known for its panoramic views over the city and the Yoshino River.
|
E627502
|
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: Mount Bizan | Statement: [Tokushima, hasMountain, Mount Bizan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Bizan Context triple: [Tokushima, hasMountain, Mount Bizan]
-
A.
Mont Bénara
Mont Bénara is the highest peak on the French Indian Ocean island of Mayotte, known for its lush tropical forests and panoramic views over the surrounding lagoon.
-
B.
Mount Balbi
Mount Balbi is an active stratovolcano and the highest peak on Bougainville Island in Papua New Guinea.
-
C.
Mont Boron
Mont Boron is a wooded hill and residential area in Nice, France, known for its panoramic views over the city and the Mediterranean coast.
-
D.
Mount Giona
Mount Giona is a prominent mountain massif in central Greece known for its rugged terrain and significant elevation among the country’s highest peaks.
-
E.
Mount Caubvick
Mount Caubvick is a prominent peak in the Torngat Mountains of eastern Canada, known for being the highest mountain in the region and a challenging destination for climbers.
- 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: Mount Bizan Triple: [Tokushima, hasMountain, Mount Bizan]
Generated description
Mount Bizan is a small, scenic mountain in Tokushima, Japan, known for its panoramic views over the city and the Yoshino River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mount Bizan Target entity description: Mount Bizan is a small, scenic mountain in Tokushima, Japan, known for its panoramic views over the city and the Yoshino River.
-
A.
Mont Bénara
Mont Bénara is the highest peak on the French Indian Ocean island of Mayotte, known for its lush tropical forests and panoramic views over the surrounding lagoon.
-
B.
Mount Balbi
Mount Balbi is an active stratovolcano and the highest peak on Bougainville Island in Papua New Guinea.
-
C.
Mont Boron
Mont Boron is a wooded hill and residential area in Nice, France, known for its panoramic views over the city and the Mediterranean coast.
-
D.
Mount Giona
Mount Giona is a prominent mountain massif in central Greece known for its rugged terrain and significant elevation among the country’s highest peaks.
-
E.
Mount Caubvick
Mount Caubvick is a prominent peak in the Torngat Mountains of eastern Canada, known for being the highest mountain in the region and a challenging destination for climbers.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8a793a481909340239c065393a4 |
completed | March 27, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748c0689081908d37d1530ed0f6a0 |
completed | March 28, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69c749741dd08190b268303a12c17b66 |
completed | March 28, 2026, 3:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74a1935b88190a9bed6e73f730459 |
completed | March 28, 2026, 3:25 a.m. |
Created at: March 27, 2026, 2:22 p.m.