Triple

T416633
Position Surface form Disambiguated ID Type / Status
Subject Karakoram E8006 entity
Predicate highestPeak P1674 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: [Karakoram, highestPeak, K2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: K2
Context triple: [Karakoram, highestPeak, 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. Tirich Mir
    Tirich Mir is a towering mountain peak in Pakistan’s Chitral region, renowned as the highest summit in the Hindu Kush range.
  • C. Kangchenjunga
    Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
  • D. Annapurna
    Annapurna is a prominent massif in north-central Nepal renowned for its towering peaks, including one of the world’s highest mountains, and its challenging trekking and climbing routes.
  • E. Dhaulagiri
    Dhaulagiri is one of the world’s highest and most prominent peaks, a massive Himalayan mountain in north-central Nepal renowned for its steep slopes and challenging climbing routes.
  • 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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ee8ea7b88190b4970b9c2877fbd8 completed Feb. 28, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69a42f6278808190be4432cf305f525c completed March 1, 2026, 12:21 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.