Triple
T16259803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karo Highlands |
E394723
|
entity |
| Predicate | hasNearbyVolcano |
P10443
|
FINISHED |
| Object | Mount Sibayak |
E594755
|
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: Mount Sibayak | Statement: [Karo Highlands, hasNearbyVolcano, Mount Sibayak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Sibayak Context triple: [Karo Highlands, hasNearbyVolcano, Mount Sibayak]
-
A.
Mount Sibayak
chosen
Mount Sibayak is an active stratovolcano in North Sumatra, Indonesia, known for its accessible crater, geothermal vents, and popular hiking trails near the town of Berastagi.
-
B.
Mount Arayat
Mount Arayat is a prominent inactive stratovolcano and pilgrimage site rising from the plains of Pampanga in Central Luzon, Philippines.
-
C.
Mount Binaiya
Mount Binaiya is the highest mountain on the Indonesian island of Seram, known for its rugged terrain and rich biodiversity.
-
D.
Mount Isarog
Mount Isarog is a prominent, forested stratovolcano in the Bicol Region of southern Luzon in the Philippines, known for its rich biodiversity and hiking trails.
-
E.
Mount Buko
Mount Buko is a prominent mountain in Japan’s Saitama Prefecture, known for its limestone quarrying and scenic hiking trails overlooking the Chichibu region.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c3082c8190a1c9f92b255fdbb6 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025f9b8bc81909315b14c3c1f6d83 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.