Triple

T6489810
Position Surface form Disambiguated ID Type / Status
Subject Cauquenes Province E148006 entity
Predicate borders P224 FINISHED
Object Linares Province E98300 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: Linares Province | Statement: [Cauquenes Province, borders, Linares Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linares Province
Context triple: [Cauquenes Province, borders, Linares Province]
  • A. Linares Province chosen
    Linares Province is an administrative division in central Chile known for its agricultural production and location within the Maule Region.
  • B. Dos de Mayo Province
    Dos de Mayo Province is an administrative province located in central Peru, within the Andean highlands of the Huánuco Region.
  • C. San Román Province
    San Román Province is an administrative division in southern Peru known for its capital city Juliaca, a major commercial and transport hub in the Andean highlands.
  • D. Espinar Province
    Espinar Province is an administrative province in southern Peru known for its high Andean geography, mining activities, and location within the Cusco Region.
  • E. Castrovirreyna Province
    Castrovirreyna Province is an administrative province in the central highlands of Peru, known for its mountainous Andean terrain and rural communities.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9926fc81909db0f390e385e97d completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c66385943081908630aa0f2cdefa06 completed March 27, 2026, 11:01 a.m.
Created at: March 22, 2026, 4:52 p.m.