Triple

T914167
Position Surface form Disambiguated ID Type / Status
Subject Chubut River E19729 entity
Predicate associatedCity P3207 FINISHED
Object Trelew E112982 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: Trelew | Statement: [Chubut River, associatedCity, Trelew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trelew
Context triple: [Chubut River, associatedCity, Trelew]
  • A. Trelew chosen
    Trelew is a city in the Chubut Province of Argentine Patagonia, known as a commercial and transportation hub with strong Welsh cultural heritage.
  • B. Puerto Natales
    Puerto Natales is a small Patagonian port town in southern Chile, best known as the main gateway to Torres del Paine National Park.
  • C. Panguipulli
    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.
  • D. Ushuaia
    Ushuaia is the southernmost city in the world, located in Argentina’s Tierra del Fuego and serving as a major gateway to Antarctic voyages.
  • E. Concepción
    Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2e196688190a7c15c9c538d0295 completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16fbe454819085020fc245c959ed completed March 7, 2026, 12:15 p.m.
Created at: March 1, 2026, 7:39 p.m.