Triple

T13076658
Position Surface form Disambiguated ID Type / Status
Subject Royal Palace Museum E329591 entity
Predicate near P350 FINISHED
Object Mount Phousi E331725 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: Mount Phousi | Statement: [Royal Palace Museum, near, Mount Phousi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Phousi
Context triple: [Royal Palace Museum, near, Mount Phousi]
  • A. Mount Phousi chosen
    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.
  • B. Mount Loilaeng
    Mount Loilaeng is a prominent peak in eastern Myanmar, recognized as the highest mountain in the Shan Hills range.
  • C. Mount Popomanaseu
    Mount Popomanaseu is the tallest mountain on the island of Guadalcanal in the Solomon Islands, known for its rugged terrain and tropical rainforest environment.
  • D. Mount Yengo
    Mount Yengo is a flat-topped mountain in New South Wales, Australia, that holds great cultural and spiritual significance for Aboriginal peoples and forms a prominent feature of Yengo National Park.
  • 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 (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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d98117209081908272021013df2222 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27058dc8190a64e1a929f296619 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:01 p.m.