Triple

T17829140
Position Surface form Disambiguated ID Type / Status
Subject Rosario Department E445202 entity
Predicate contains P35 FINISHED
Object Rosario
Rosario is a major Argentine city in the province of Santa Fe, known as an important industrial, commercial, and port center on the Paraná River.
 E99633 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: Rosario | Statement: [Rosario Department, contains, Rosario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rosario
Context triple: [Rosario Department, contains, Rosario]
  • A. Rosario
    Rosario is a major Argentine port city and industrial center located in the province of Santa Fe.
  • B. Rosario
    Rosario is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • C. Rosario
    Rosario is a feminine given name of Spanish and Italian origin, commonly associated with the Roman Catholic devotion to the Rosary.
  • D. Rosario
    Rosario is a first-class agricultural municipality in the province of Batangas in the Philippines, known for its coconut and rice farming.
  • E. Rosario
    Rosario is a prestigious private university in Bogotá, Colombia, known for its historic role in the country’s political and academic life.
  • 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: Rosario
Triple: [Rosario Department, contains, Rosario]
Generated description
Rosario is a major Argentine city in the province of Santa Fe, known as an important industrial, commercial, and port center on the Paraná River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rosario
Target entity description: Rosario is a major Argentine city in the province of Santa Fe, known as an important industrial, commercial, and port center on the Paraná River.
  • A. Rosario chosen
    Rosario is a major Argentine port city and industrial center located in the province of Santa Fe.
  • B. Rosario
    Rosario is a coastal municipality in the Mexican state of Sinaloa known for its historic architecture, mining heritage, and proximity to the Pacific Ocean.
  • C. Rosario
    Rosario is a coastal municipality in the province of Cavite in the Philippines, known for its fishing industry and proximity to Manila Bay.
  • D. Rosario
    Rosario is a first-class agricultural municipality in the province of Batangas in the Philippines, known for its coconut and rice farming.
  • E. Rosario
    Rosario is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • F. None of above.

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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4891696cc819092ee6db7c4a6fae1 completed April 19, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a031b18f3308190a847d0922c090fdb completed May 12, 2026, 12:20 p.m.
NEDg Description generation batch_6a031c3658988190b59fa17d616cad9b completed May 12, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a031c9914dc819099da3b2174a5fbc7 completed May 12, 2026, 12:27 p.m.
Created at: April 10, 2026, 10:15 a.m.