Triple

T19316661
Position Surface form Disambiguated ID Type / Status
Subject Lake Pellaifa E483115 entity
Predicate locatedNear P294 FINISHED
Object Panguipulli NE NERFINISHED

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: Panguipulli | Statement: [Lake Pellaifa, locatedNear, Panguipulli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Panguipulli
Context triple: [Lake Pellaifa, locatedNear, Panguipulli]
  • A. Panguipulli chosen
    Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
  • B. San Rafael del Sur
    San Rafael del Sur is a town in Nicaragua that serves as the administrative and commercial center of the surrounding San Rafael del Sur Municipality.
  • C. Ossorio
    Ossorio is a Spanish-origin surname notably borne by Filipino-American abstract expressionist artist Alfonso Ossorio.
  • D. Belén de los Andaquíes
    Belén de los Andaquíes is a small municipality in southern Colombia known for its Amazonian rainforest environment and location within the Caquetá Department.
  • E. Tocancipá
    Tocancipá is a Colombian municipality in the department of Cundinamarca, known for its industrial activity, motorsport circuit, and proximity to Bogotá.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e60d843640819089ff3738aae29eb1 completed April 20, 2026, 11:27 a.m.
Created at: April 10, 2026, 1:32 p.m.