Triple

T6081697
Position Surface form Disambiguated ID Type / Status
Subject Ribbon Fall E135537 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: [Ribbon Fall, mountainRange, Sierra Nevada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sierra Nevada
Context triple: [Ribbon Fall, 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 renowned video game company best known for its pioneering graphic adventure games and influential role in the early PC gaming industry.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05774bc948190a446b27e83f7079b completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c12510695c8190a8c379c9802a9089 completed March 23, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:11 p.m.