Triple

T4157176
Position Surface form Disambiguated ID Type / Status
Subject Thomas Roupell Everest E91442 entity
Predicate notableRelative P367 FINISHED
Object George Everest E97375 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: George Everest | Statement: [Thomas Roupell Everest, notableRelative, George Everest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Everest
Context triple: [Thomas Roupell Everest, notableRelative, George Everest]
  • A. George Everest chosen
    George Everest was a 19th-century British surveyor and geographer who served as Surveyor General of India and lent his name to Mount Everest.
  • B. Everest
    Everest is the codename for the high-performance CPU cores used in Apple’s A16 Bionic chip.
  • C. 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.
  • D. Shkhara
    Shkhara is a prominent peak in the Greater Caucasus mountain range, known as one of the highest and most challenging mountains in the region.
  • E. Kangchenjunga
    Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
  • 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_69aed9626ebc8190a39de631788bea3e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af028fc11c819093fb2f616b97a694 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589e9ff288190a8dfb62d32a330b5 completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:44 p.m.