Triple
T247212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Himalayas |
E5063
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | K2 |
E9638
|
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: K2 | Statement: [Himalayas, contains, K2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K2 Context triple: [Himalayas, contains, K2]
-
A.
K2
chosen
K2 is the world’s second-highest mountain, a notoriously difficult and dangerous peak in the Karakoram range of the Himalayas.
-
B.
Mount Everest
Mount Everest is the world's highest mountain above sea level, located in the Himalayas on the border between Nepal and the Tibet Autonomous Region of China.
-
C.
Karakoram
Karakoram is a major mountain range in Central and South Asia, home to some of the world’s highest peaks including K2 and extensive glaciers.
-
D.
Hindu Kush
The Hindu Kush is a major mountain range in Central and South Asia, forming a rugged extension of the Himalayas and serving as a historic crossroads between the Indian subcontinent and the Middle East.
-
E.
Nevis
Nevis is a small volcanic island in the Caribbean known for its lush landscapes, historic plantations, and tranquil beaches.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d13b8088190a3f48f0388d57496 |
completed | Feb. 28, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3765be530819088d680acc6a26a4a |
completed | Feb. 28, 2026, 11:12 p.m. |
Created at: Feb. 28, 2026, 2:54 a.m.