Triple

T899692
Position Surface form Disambiguated ID Type / Status
Subject Río Negro E19418 entity
Predicate flowsThrough P225 FINISHED
Object Cipolletti
Cipolletti is a city in Argentina’s Patagonia region, known as an important agricultural and service center in the Alto Valle of the Río Negro.
 E138479 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: Cipolletti | Statement: [Río Negro, flowsThrough, Cipolletti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cipolletti
Context triple: [Río Negro, flowsThrough, Cipolletti]
  • A. Río Bueno
    Río Bueno is a Chilean city known for its agricultural surroundings and location along the Bueno River in the Los Ríos Region.
  • B. Lago Ranco
    Lago Ranco is a small town in southern Chile known for its scenic setting on the shores of Lake Ranco in the Los Ríos Region.
  • C. Curanilahue
    Curanilahue is a Chilean city and commune in the Biobío Region, known historically for its coal mining industry and location in the Arauco Province.
  • D. Quirihue
    Quirihue is a small city in central Chile that serves as the capital of the Itata Province in the Ñuble Region.
  • E. Chañaral
    Chañaral is a coastal city in northern Chile known historically for its mining activity and its location along the Atacama Desert shoreline.
  • 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: Cipolletti
Triple: [Río Negro, flowsThrough, Cipolletti]
Generated description
Cipolletti is a city in Argentina’s Patagonia region, known as an important agricultural and service center in the Alto Valle of the Río Negro.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cipolletti
Target entity description: Cipolletti is a city in Argentina’s Patagonia region, known as an important agricultural and service center in the Alto Valle of the Río Negro.
  • A. Río Bueno
    Río Bueno is a Chilean city known for its agricultural surroundings and location along the Bueno River in the Los Ríos Region.
  • B. Lago Ranco
    Lago Ranco is a small town in southern Chile known for its scenic setting on the shores of Lake Ranco in the Los Ríos Region.
  • C. Curanilahue
    Curanilahue is a Chilean city and commune in the Biobío Region, known historically for its coal mining industry and location in the Arauco Province.
  • D. Quirihue
    Quirihue is a small city in central Chile that serves as the capital of the Itata Province in the Ñuble Region.
  • E. Chañaral
    Chañaral is a coastal city in northern Chile known historically for its mining activity and its location along the Atacama Desert shoreline.
  • 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_69ac7f23e10081909ebf4e87dc081254 completed March 7, 2026, 7:40 p.m.
NEDg Description generation batch_69ac7f9a55dc819098204d53aac70ef3 completed March 7, 2026, 7:42 p.m.
NED2 Entity disambiguation (via description) batch_69ac80c3c6b08190a99119f5661c0157 completed March 7, 2026, 7:47 p.m.
Created at: March 1, 2026, 7:39 p.m.