Triple

T22706035
Position Surface form Disambiguated ID Type / Status
Subject Alto Paraguay Department E561454 entity
Predicate hasTown P847 FINISHED
Object Puerto Casado 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: Puerto Casado | Statement: [Alto Paraguay Department, hasTown, Puerto Casado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Casado
Context triple: [Alto Paraguay Department, hasTown, Puerto Casado]
  • A. Puerto Casado chosen
    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.
  • B. Puerto San José
    Puerto San José is a Pacific coastal port town in Guatemala known for its beaches, fishing, and role as a gateway to nearby tourist destinations.
  • C. Puerto Marqués
    Puerto Marqués is a coastal bay and beach community near Acapulco in the Mexican state of Guerrero, known for its calm waters and tourism.
  • D. Puerto Galván
    Puerto Galván is a port locality within the Bahía Blanca area of Buenos Aires Province, Argentina, known for its industrial and maritime activities.
  • E. Puerto Blest
    Puerto Blest is a small lakeside settlement and tourist port in Argentina’s Nahuel Huapi National Park, known as a gateway to scenic boat excursions and Andean forest landscapes.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178ceba6c8190a538366a8e4648de completed April 29, 2026, 3:19 a.m.
Created at: April 17, 2026, 3:17 p.m.