Triple

T5848177
Position Surface form Disambiguated ID Type / Status
Subject Sinai Desert E129763 entity
Predicate highestPoint P210 FINISHED
Object Mount Catherine E44271 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 Catherine | Statement: [Sinai Desert, highestPoint, Mount Catherine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Catherine
Context triple: [Sinai Desert, highestPoint, Mount Catherine]
  • A. Mount Catherine chosen
    Mount Catherine is the highest mountain in Egypt, located in the southern Sinai Peninsula and known for its rugged terrain and religious significance.
  • B. Mount Harriet
    Mount Harriet is a notable peak in the Falkland Islands that gained prominence as a key location during the 1982 Falklands War.
  • C. Mount Sentinel
    Mount Sentinel is a prominent mountain peak within Australia's Snowy Mountains region, known for its rugged alpine terrain and scenic vistas.
  • D. Mount Ainslie
    Mount Ainslie is a prominent hill in Canberra, Australia, known for its popular lookout offering panoramic views over the city and its surrounding landscape.
  • E. Cypress Mountain
    Cypress Mountain is a ski resort in West Vancouver, British Columbia, known for hosting the freestyle skiing and snowboarding events during the 2010 Winter Olympics.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03512d3548190920ac882189500d9 completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1ad4d888190b4a1e605887b2e2c completed March 23, 2026, 2:13 a.m.
Created at: March 22, 2026, 3:55 p.m.