Triple
T7528311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont Orohena |
E177951
|
entity |
| Predicate | hasMapLabel |
P13793
|
FINISHED |
| Object | Mont Orohena |
E177951
|
NE 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: Mont Orohena | Statement: [Mont Orohena, hasMapLabel, Mont Orohena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mont Orohena Context triple: [Mont Orohena, hasMapLabel, Mont Orohena]
-
A.
Mont Orohena
chosen
Mont Orohena is a volcanic mountain in French Polynesia and the tallest peak on the island of Tahiti.
-
B.
Mount Haruna
Mount Haruna is an active stratovolcano in Gunma Prefecture, Japan, known for its scenic caldera lake, hot springs, and popular hiking and sightseeing spots.
-
C.
Kurohime-yama
Kurohime-yama is a subsidiary peak of Japan’s Mount Akagi, known as part of the volcanic mountain’s multi-summit range in Gunma Prefecture.
-
D.
Kurohime-yama
Kurohime-yama is a mountain in Japan, known for its scenic landscapes and popular hiking and skiing opportunities.
-
E.
Mount Kinka
Mount Kinka is a prominent forested mountain in Gifu, Japan, known for its scenic views, hiking trails, and the historic Gifu Castle at its summit.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81e19208190965f211d057f7fdf |
completed | March 27, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c86834713481908400504fb7b49068 |
completed | March 28, 2026, 11:45 p.m. |
Created at: March 27, 2026, 3:47 p.m.