Triple

T19226341
Position Surface form Disambiguated ID Type / Status
Subject Litoral region E480746 entity
Predicate hasMajorCity P316 FINISHED
Object Rosario
Rosario is a major Argentine port city on the Paraná River, known as an industrial and commercial hub and the birthplace of the national flag.
 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: [Litoral region, hasMajorCity, Rosario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rosario
Context triple: [Litoral region, hasMajorCity, Rosario]
  • A. Rosario
    Rosario is a prestigious private university in Bogotá, Colombia, known for its historic role in the country’s political and academic life.
  • B. Rosario
    Rosario is a coastal municipality in the province of Cavite in the Philippines, known for its fishing industry and proximity to Manila Bay.
  • 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 coastal municipality in the Mexican state of Sinaloa known for its historic architecture, mining heritage, and proximity to the Pacific Ocean.
  • 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. 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: [Litoral region, hasMajorCity, Rosario]
Generated description
Rosario is a major Argentine port city on the Paraná River, known as an industrial and commercial hub and the birthplace of the national flag.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rosario
Target entity description: Rosario is a major Argentine port city on the Paraná River, known as an industrial and commercial hub and the birthplace of the national flag.
  • 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 feminine given name of Spanish and Italian origin, commonly associated with the Roman Catholic devotion to the Rosary.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa988afc81909c6a751a148bea16 completed April 20, 2026, 10:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0700f0bf24819081472a1849edf6db completed May 15, 2026, 11:18 a.m.
NEDg Description generation batch_6a070191a48481908f2c731d0d1d00bf completed May 15, 2026, 11:20 a.m.
NED2 Entity disambiguation (via description) batch_6a07025e91488190a25f6eb4fd6916c2 completed May 15, 2026, 11:24 a.m.
Created at: April 10, 2026, 1:24 p.m.