Triple

T4828912
Position Surface form Disambiguated ID Type / Status
Subject Osorno Volcano E107894 entity
Predicate nearCity P350 FINISHED
Object Puerto Varas E128025 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: Puerto Varas | Statement: [Osorno Volcano, nearCity, Puerto Varas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Varas
Context triple: [Osorno Volcano, nearCity, Puerto Varas]
  • A. Puerto Varas chosen
    Puerto Varas is a picturesque lakeside city in southern Chile’s Los Lagos Region, known for its German-influenced architecture and views of the Osorno and Calbuco volcanoes.
  • B. Los Lagos
    Los Lagos is a small Chilean city located in the Los Ríos Region, known for its riverside setting and role as a local agricultural and forestry center.
  • C. Los Lagos
    Los Lagos is a region in southern Chile known for its numerous lakes, volcanoes, and lush temperate rainforests.
  • D. Puerto Montt
    Puerto Montt is a port city in southern Chile, serving as a key gateway to the Patagonian fjords and the Chilean Lake District.
  • E. Vallenar
    Vallenar is a city in northern Chile known as an agricultural and mining center in the Atacama Desert.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cc3dc0481909c8884dbe5043a71 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf186311c88190a8fe34e497e4662b completed March 21, 2026, 10:14 p.m.
Created at: March 20, 2026, 1:24 p.m.