Triple

T765629
Position Surface form Disambiguated ID Type / Status
Subject Mary Everest Boole E16169 entity
Predicate relative P37 FINISHED
Object George Everest E91442 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: [Mary Everest Boole, relative, George Everest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Everest
Context triple: [Mary Everest Boole, relative, George Everest]
  • A. 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.
  • B. Kangchenjunga
    Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
  • C. Thomas Roupell Everest chosen
    Thomas Roupell Everest was a 19th-century English clergyman and writer, best known today as the father of mathematician and educationalist Mary Everest Boole.
  • D. Cho Oyu
    Cho Oyu is the world’s sixth-highest mountain, an 8,188-meter peak in the Mahalangur Himal section of the Himalayas near the Nepal–China border.
  • E. Nanga Parbat
    Nanga Parbat is one of the world’s highest and most notoriously challenging mountains, located in the western Himalayas of Pakistan.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a69fb6ac8190bda41852ea01842c completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a67efa8dd481909097c551bf3a61dc completed March 3, 2026, 6:26 a.m.
Created at: March 1, 2026, 7:37 p.m.