Triple

T9694073
Position Surface form Disambiguated ID Type / Status
Subject Huilliche E234603 entity
Predicate traditionalTerritory P1103 FINISHED
Object Osorno Province E124423 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: Osorno Province | Statement: [Huilliche, traditionalTerritory, Osorno Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osorno Province
Context triple: [Huilliche, traditionalTerritory, Osorno Province]
  • A. Osorno Province chosen
    Osorno Province is an administrative division in southern Chile known for its agricultural activity, lakes, and proximity to the Andes and volcanoes.
  • B. Cutervo Province
    Cutervo Province is an administrative subdivision in northern Peru known for its mountainous terrain, rural communities, and proximity to the Cutervo National Park.
  • C. Melgar Province
    Melgar Province is an administrative division in southeastern Peru known for its high Andean landscapes and location within the Puno Region.
  • D. Celendín Province
    Celendín Province is an administrative division in northern Peru known for its Andean landscapes, rural communities, and traditional highland culture.
  • E. Muñecas Province
    Muñecas Province is an administrative subdivision in the northern part of Bolivia’s La Paz Department, known for its rural Andean communities and mountainous terrain.
  • 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d348868819083aec7a5da8c455b completed April 1, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1911d33f081908637cbf4c1949bcd completed April 4, 2026, 10:30 p.m.
Created at: March 30, 2026, 8:17 p.m.