Triple

T20098766
Position Surface form Disambiguated ID Type / Status
Subject Fatu Hiva E496476 entity
Predicate hasHighestPoint P210 FINISHED
Object Mount Touaouoho 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 Touaouoho | Statement: [Fatu Hiva, hasHighestPoint, Mount Touaouoho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Touaouoho
Context triple: [Fatu Hiva, hasHighestPoint, Mount Touaouoho]
  • A. Mont Touaouoho chosen
    Mont Touaouoho is the principal mountain peak on the remote Polynesian island of Fatu Hiva in the Marquesas Islands of French Polynesia.
  • B. Mount Phousi
    Mount Phousi is a prominent hill in the center of Luang Prabang, Laos, known for its Buddhist shrines and panoramic views of the city and Mekong River.
  • C. Mount Loilaeng
    Mount Loilaeng is a prominent peak in eastern Myanmar, recognized as the highest mountain in the Shan Hills range.
  • D. Mount Vineuo
    Mount Vineuo is the tallest mountain on the D'Entrecasteaux Islands of Papua New Guinea, known for its prominent peak and rugged terrain.
  • E. Mount Heha
    Mount Heha is the tallest mountain in Burundi, located in the Burundi Highlands near the city of Bujumbura.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6666e306c81909c0ef617e0f6fccf completed April 20, 2026, 5:46 p.m.
Created at: April 11, 2026, 11:25 p.m.