Triple
T23365545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Prem |
E593308
|
entity |
| Predicate | notableAscent |
P6286
|
FINISHED |
| Object | Sajama |
—
|
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: Sajama | Statement: [Joseph Prem, notableAscent, Sajama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sajama Context triple: [Joseph Prem, notableAscent, Sajama]
-
A.
Sajama
chosen
Sajama is the highest mountain in Bolivia, an extinct stratovolcano located in the Andes near the Chilean border.
-
B.
Illimani
Illimani is a towering, snow-capped mountain in the Bolivian Andes that serves as an iconic natural landmark visible from the city of La Paz.
-
C.
Monte Venda
Monte Venda is the tallest peak in Italy’s Euganean Hills, known for its forested slopes and panoramic views over the surrounding Veneto countryside.
-
D.
Chimbel
Chimbel is a village in North Goa, India, known for its proximity to the state capital Panaji and its rapidly urbanizing residential character.
-
E.
Mount Saramati
Mount Saramati is a prominent peak in Northeast India, known for its rugged terrain, rich biodiversity, and panoramic views over the India–Myanmar border region.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0ab7fc481908b496ec9b543eddd |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 17, 2026, 5:31 p.m.