Triple

T4655464
Position Surface form Disambiguated ID Type / Status
Subject Panguilemo Airport E102397 entity
Predicate serves P98 FINISHED
Object Maule Region E17708 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: Maule Region | Statement: [Panguilemo Airport, serves, Maule Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maule Region
Context triple: [Panguilemo Airport, serves, Maule Region]
  • A. Maule Region chosen
    The Maule Region is an administrative region in central Chile known for its agricultural production, wine industry, and coastal and Andean landscapes.
  • B. Los Lagos Region
    Los Lagos Region is a southern administrative region of Chile known for its lakes, volcanoes, and coastal landscapes, including the island of Chiloé.
  • C. Región de Ñuble
    Región de Ñuble is an administrative region in central Chile known for its agricultural production, wine valleys, and the city of Chillán as its capital.
  • D. O’Higgins Region
    The O’Higgins Region is an administrative region in central Chile known for its agricultural production, particularly vineyards and fruit growing, and its capital city, Rancagua.
  • E. Maule Valley
    Maule Valley is a prominent wine-producing region in central Chile, known for its diverse terroir and significant output of red and white varietals.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6317ba70819089145766d3462e57 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfc60964c08190bcb128946e121bc9 completed March 22, 2026, 10:35 a.m.
Created at: March 20, 2026, 1:14 p.m.