Triple

T15778372
Position Surface form Disambiguated ID Type / Status
Subject Camacho Province E382545 entity
Predicate hasSettlement P1068 FINISHED
Object Puerto Acosta E1177443 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 Acosta | Statement: [Camacho Province, hasSettlement, Puerto Acosta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Acosta
Context triple: [Camacho Province, hasSettlement, Puerto Acosta]
  • A. Puerto Acosta chosen
    Puerto Acosta is a small Bolivian town in the La Paz Department, situated near Lake Titicaca and serving as an administrative and commercial center for the surrounding rural region.
  • B. Puerto Díaz
    Puerto Díaz is a small lakeside settlement in Nicaragua located near Zapatera Island in Lake Nicaragua.
  • C. Puerto Tejada
    Puerto Tejada is a Colombian city in the Cauca Department known for its Afro-Colombian cultural heritage and agricultural-based economy.
  • D. Puerto Casado
    Puerto Casado is a small river port town in northern Paraguay known historically for its tannin industry and its strategic location on the Paraguay River.
  • E. Puerto Octay
    Puerto Octay is a small Chilean town in the Los Lagos Region, known for its German-influenced architecture, scenic views, and tourism centered around nearby lakes and volcanoes.
  • 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e05199cd8881909462462cec34d35a completed April 16, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff998559088190b1f2942564a42ace completed May 9, 2026, 8:31 p.m.
Created at: April 10, 2026, 4:47 a.m.