Triple

T16645472
Position Surface form Disambiguated ID Type / Status
Subject Cottonwood Pass E404456 entity
Predicate connects P390 FINISHED
Object Buena Vista E469123 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: Buena Vista | Statement: [Cottonwood Pass, connects, Buena Vista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buena Vista
Context triple: [Cottonwood Pass, connects, Buena Vista]
  • A. Buena Vista
    Buena Vista is a small city in Marion County, Georgia, known as a rural community in the west-central part of the state.
  • B. Buena Vista
    Buena Vista is a brand name historically used by The Walt Disney Company for its international film distribution and related entertainment operations.
  • C. Buena Vista chosen
    Buena Vista is a small mountain town in central Colorado known for its outdoor recreation, especially whitewater rafting on the Arkansas River and access to the Collegiate Peaks.
  • D. Buena Vista
    Buena Vista is a historic battlefield in northern Mexico best known as the site of a major American victory during the Mexican–American War.
  • E. Buona Vista
    Buona Vista is a district in western Singapore known for its technology hubs, research institutions, and mixed residential-commercial developments.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad4735c81908a3a227bf02ca489 completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084bf0900819092db11456eb8e1c0 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:18 a.m.