Triple

T9096895
Position Surface form Disambiguated ID Type / Status
Subject Mount Farquhar E218047 entity
Predicate mountainRange P648 FINISHED
Object Sierra Nevada E245 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: Sierra Nevada | Statement: [Mount Farquhar, mountainRange, Sierra Nevada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sierra Nevada
Context triple: [Mount Farquhar, mountainRange, Sierra Nevada]
  • A. Sierra Nevada chosen
    Sierra Nevada is a major mountain range in the western United States known for its dramatic granite peaks, extensive forests, and iconic natural landmarks such as Yosemite National Park and Lake Tahoe.
  • B. Sierra Nevada
    Sierra Nevada is a prominent mountain range in southern Spain known for its high peaks, ski resorts, and inclusion in a national park.
  • C. Sierra
    Sierra is one of the central "Actives" in the TV series *Dollhouse*, known for her complex backstory and evolving sense of identity amid the show's mind-wiping technology.
  • D. Sierra
    Sierra is the Andean highland natural region of Peru, characterized by mountainous terrain, high plateaus, and a cool climate.
  • E. Sierra
    Sierra is a residential neighborhood within the master-planned Great Park Neighborhoods community in Irvine, California.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b7d0d48190a3b15f35bef087e3 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0479a58c48190acd4a4af21aa01c3 completed April 3, 2026, 11:04 p.m.
Created at: March 30, 2026, 7:15 p.m.