Triple

T899695
Position Surface form Disambiguated ID Type / Status
Subject Río Negro E19418 entity
Predicate flowsThrough P225 FINISHED
Object Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
 E106861 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: Viedma | Statement: [Río Negro, flowsThrough, Viedma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Viedma
Context triple: [Río Negro, flowsThrough, Viedma]
  • A. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • B. Lielupe
    Lielupe is a major river in central Latvia that flows into the Gulf of Riga and is known for its wide floodplain and role in regional agriculture and transport.
  • C. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • D. Hiiumaa
    Hiiumaa is Estonia’s second-largest island, located in the Baltic Sea and known for its unspoiled nature, lighthouses, and quiet rural landscapes.
  • E. Sudetes
    The Sudetes are a mountain range in Central Europe spanning parts of Poland, the Czech Republic, and Germany, known for their forested peaks, mineral resources, and popular spa and ski resorts.
  • 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: Viedma
Triple: [Río Negro, flowsThrough, Viedma]
Generated description
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Viedma
Target entity description: Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
  • A. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • B. Lielupe
    Lielupe is a major river in central Latvia that flows into the Gulf of Riga and is known for its wide floodplain and role in regional agriculture and transport.
  • C. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • D. Hiiumaa
    Hiiumaa is Estonia’s second-largest island, located in the Baltic Sea and known for its unspoiled nature, lighthouses, and quiet rural landscapes.
  • E. Sudetes
    The Sudetes are a mountain range in Central Europe spanning parts of Poland, the Czech Republic, and Germany, known for their forested peaks, mineral resources, and popular spa and ski resorts.
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad4162848190aa2787b2fa3e6575 completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c734e680819098840e9c736b5ead completed March 4, 2026, 5:46 a.m.
NEDg Description generation batch_69a7c8a3064081908772ee2305bbe3e1 completed March 4, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_69a7c8fecaac8190a7b1a1cd2fa98a2d completed March 4, 2026, 5:54 a.m.
Created at: March 1, 2026, 7:39 p.m.