Triple

T36023792
Position Surface form Disambiguated ID Type / Status
Subject Córdoba river system E1042065 entity
Predicate hasInfrastructure P2560 FINISHED
Object La Viña Dam
La Viña Dam is a large hydroelectric and irrigation dam in Córdoba Province, Argentina, known for forming a popular reservoir used for water supply, power generation, and recreation.
E2175591 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: La Viña Dam | Statement: [Córdoba river system, hasInfrastructure, La Viña Dam]
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: La Viña Dam
Triple: [Córdoba river system, hasInfrastructure, La Viña Dam]
Generated description
La Viña Dam is a large hydroelectric and irrigation dam in Córdoba Province, Argentina, known for forming a popular reservoir used for water supply, power generation, and recreation.

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_69f76e2c568881909e1e21f85252b0f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ace54a18819089854ef1116f199f completed May 3, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d1e1ad881908635115d8f109997 completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a394f909b288190997434da2588da03 completed June 22, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_6a39505da1848190b4b631c9829d1b31 completed June 22, 2026, 3:10 p.m.
Created at: May 3, 2026, 4:07 p.m.