Triple

T22551512
Position Surface form Disambiguated ID Type / Status
Subject Rocha Department E557567 entity
Predicate contains P35 FINISHED
Object Aguas Dulces
Aguas Dulces is a small coastal resort town and beach destination on Uruguay’s Atlantic coast, known for its relaxed atmosphere and sand dunes.
 E1542577 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: Aguas Dulces | Statement: [Rocha Department, contains, Aguas Dulces]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aguas Dulces
Context triple: [Rocha Department, contains, Aguas Dulces]
  • A. Aguadulce
    Aguadulce is a coastal town in the province of Almería in southeastern Spain, known for its beaches, marina, and tourism-oriented seafront.
  • B. Aguadulce
    Aguadulce is a city in central Panama known as an agricultural and commercial hub, particularly for sugar and salt production.
  • C. Aguada
    Aguada is a coastal municipality on Puerto Rico’s west coast known for its beaches and role as a regional commercial and transportation hub.
  • D. Aguas Verdes
    Aguas Verdes is a Peruvian border town known as a busy commercial crossing point between Peru and Ecuador near the city of Tumbes.
  • E. Nahualá
    Nahualá is a predominantly Kʼicheʼ Maya town and municipality in Guatemala known for its strong indigenous traditions and highland agricultural economy.
  • 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: Aguas Dulces
Triple: [Rocha Department, contains, Aguas Dulces]
Generated description
Aguas Dulces is a small coastal resort town and beach destination on Uruguay’s Atlantic coast, known for its relaxed atmosphere and sand dunes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aguas Dulces
Target entity description: Aguas Dulces is a small coastal resort town and beach destination on Uruguay’s Atlantic coast, known for its relaxed atmosphere and sand dunes.
  • A. Aguadulce
    Aguadulce is a coastal town in the province of Almería in southeastern Spain, known for its beaches, marina, and tourism-oriented seafront.
  • B. Aguadulce
    Aguadulce is a city in central Panama known as an agricultural and commercial hub, particularly for sugar and salt production.
  • C. Aguada
    Aguada is a coastal municipality on Puerto Rico’s west coast known for its beaches and role as a regional commercial and transportation hub.
  • D. Aguas Verdes
    Aguas Verdes is a Peruvian border town known as a busy commercial crossing point between Peru and Ecuador near the city of Tumbes.
  • E. Nahualá
    Nahualá is a predominantly Kʼicheʼ Maya town and municipality in Guatemala known for its strong indigenous traditions and highland agricultural economy.
  • 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_69e11e59db848190b4272ecd2b690ffd completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f7647208190a1aaebd083bf095a completed April 29, 2026, 1:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b2d6309d481909185ea6ebaf80d64 completed May 18, 2026, 3:16 p.m.
NEDg Description generation batch_6a0b364718308190937c3b7ae90ea9df completed May 18, 2026, 3:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0b37998f888190bb53c2429760321a completed May 18, 2026, 4 p.m.
Created at: April 16, 2026, 8:52 p.m.