Triple
T19967161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douglas Freshfield |
E479966
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Round Kangchenjunga |
—
|
NE NERFINISHED |
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: Round Kangchenjunga | Statement: [Douglas Freshfield, notableWork, Round Kangchenjunga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Round Kangchenjunga Context triple: [Douglas Freshfield, notableWork, Round Kangchenjunga]
-
A.
Kangchenjunga
chosen
Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
-
B.
Makalu
Makalu is the fifth-highest mountain in the world, a prominent 8,485-meter peak on the border between Nepal and China known for its steep faces and challenging climbing routes.
-
C.
Gyachung Kang
Gyachung Kang is a prominent Himalayan mountain peak, one of the world’s highest, located between Nepal and China in the Mahalangur Himal range.
-
D.
Kinnauri
Kinnauri is a Tibeto-Burman language spoken primarily by the indigenous people of India’s Himalayan Kinnaur region.
-
E.
Shishapangma
Shishapangma is one of the world’s fourteen eight-thousanders, a major Himalayan peak located entirely within Tibet, China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
Created at: April 10, 2026, 1:54 p.m.