Triple

T738647
Position Surface form Disambiguated ID Type / Status
Subject Lake Nicaragua E14992 entity
Predicate hasCityOnShore P969 FINISHED
Object Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
E102655 NE FINISHED

How this triple was built (4 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: Rivas | Statement: [Lake Nicaragua, hasCityOnShore, Rivas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rivas
Context triple: [Lake Nicaragua, hasCityOnShore, Rivas]
  • A. Durán
    Durán is an Ecuadorian city in the Guayas Province, located across the Guayas River from Guayaquil and serving as an important transport and industrial hub.
  • B. Cervera
    Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
  • C. León
    León is a historic city and former kingdom in northwestern Spain, renowned for its medieval architecture and significant role in the formation of the Spanish state.
  • D. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • E. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rivas
Triple: [Lake Nicaragua, hasCityOnShore, Rivas]
Generated description
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rivas
Target entity description: Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
  • A. Durán
    Durán is an Ecuadorian city in the Guayas Province, located across the Guayas River from Guayaquil and serving as an important transport and industrial hub.
  • B. Cervera
    Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
  • C. León
    León is a historic city and former kingdom in northwestern Spain, renowned for its medieval architecture and significant role in the formation of the Spanish state.
  • D. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • E. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • F. None of above. chosen

Provenance (5 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f1c9888190b2817138c6893cfe completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3aacc788190b79623c86b2a5fe7 completed March 4, 2026, 3:14 a.m.
NEDg Description generation batch_69a7a5f0f5e08190b6eed2d8ca594cea completed March 4, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69a7a64ee7e08190907a9e28994cc4d2 completed March 4, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:37 p.m.