Triple

T2823164
Position Surface form Disambiguated ID Type / Status
Subject 1978 FIFA World Cup E54856 entity
Predicate hostCity P1798 FINISHED
Object Rosario E99633 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: Rosario | Statement: [1978 FIFA World Cup, hostCity, Rosario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosario
Context triple: [1978 FIFA World Cup, hostCity, Rosario]
  • 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. El Rosario
    El Rosario is a municipality on the island of Tenerife in Spain’s Canary Islands, known for its coastal landscapes and proximity to the island’s capital, Santa Cruz de Tenerife.
  • D. El Rosario
    El Rosario is a major Mexico City transit hub and neighborhood that serves as a key terminus and interchange point for multiple public transportation lines.
  • E. De Rosario
    De Rosario is the surname of Dwayne De Rosario, a prominent Canadian former professional soccer player known for his goal-scoring and playmaking in Major League Soccer.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde71fdc08190b18660261fe24adf completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afceaa45e88190a9007885cf7868ef completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.