Triple

T19609299
Position Surface form Disambiguated ID Type / Status
Subject East Sakhalin Mountains E470686 entity
Predicate highestPoint P210 FINISHED
Object Mount Lopatin 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: Mount Lopatin | Statement: [East Sakhalin Mountains, highestPoint, Mount Lopatin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Lopatin
Context triple: [East Sakhalin Mountains, highestPoint, Mount Lopatin]
  • A. Mount Lopatin chosen
    Mount Lopatin is the tallest mountain on Russia’s Sakhalin Island, notable as the island’s highest natural peak.
  • B. Mount Karpinsky
    Mount Karpinsky is a prominent peak in the Ural Mountains of Russia, known as one of the higher summits in the range and a notable destination for mountaineers and hikers.
  • C. Mount Narodnaya
    Mount Narodnaya is a prominent peak in Russia known as the tallest mountain in the Ural range, marking the natural boundary between Europe and Asia.
  • D. Maritsa Peak
    Maritsa Peak is a mountain summit whose slopes give rise to the Maritsa River, one of the major rivers of the Balkans.
  • E. Korzhenevskaya Peak
    Korzhenevskaya Peak is one of the highest mountains in the Pamir range of Tajikistan, renowned among climbers as a prominent seven-thousander of Central Asia.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640ca57a081909c05000fca52271f completed April 20, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:43 p.m.