Triple

T14607889
Position Surface form Disambiguated ID Type / Status
Subject Lota Bajo historic district E342879 entity
Predicate partOf P40 FINISHED
Object city of Lota E68423 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: city of Lota | Statement: [Lota Bajo historic district, partOf, city of Lota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Lota
Context triple: [Lota Bajo historic district, partOf, city of Lota]
  • A. Lota chosen
    Lota is a coastal city in southern Chile known historically for its coal mining industry and maritime heritage.
  • B. City of Los Vilos
    The City of Los Vilos is a coastal urban center in Chile known for its fishing activities, beaches, and role as a local commercial hub.
  • C. city of La Serena
    The city of La Serena is a historic coastal city in northern Chile known for its colonial architecture, beaches, and role as a regional economic and cultural center.
  • D. city of Porvenir
    The city of Porvenir is the principal urban center and capital of the Chilean province of Tierra del Fuego, located on the island’s northern coast in southern Patagonia.
  • E. Mima City
    Mima City is a municipality in western Tokushima Prefecture, Japan, known for its historic townscapes, traditional indigo dyeing culture, and scenic rural landscapes.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44d327c8190a8d20568429d0f80 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d09e988190a2a2a1332397b412 completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.