Triple

T5507444
Position Surface form Disambiguated ID Type / Status
Subject Rio E144475 entity
Predicate alias P39 FINISHED
Object Rio unclear NED1 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: Rio | Statement: [Rio, alias, Rio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio
Context triple: [Rio, alias, Rio]
  • A. Rio
    Rio is a settlement located within the municipality of Elba, an island in the Tyrrhenian Sea off the coast of Italy.
  • B. Rio
    Rio is a 2011 animated adventure-comedy film set in Brazil that follows a domesticated macaw’s journey of self-discovery amid vibrant music and colorful Rio de Janeiro scenery.
  • C. Rio
    Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
  • D. Paraná River
    The Paraná River is one of South America's longest and most important rivers, flowing through Brazil, Paraguay, and Argentina and serving as a key waterway for transport, hydroelectric power, and regional ecosystems.
  • E. Paraguay River
    The Paraguay River is a major South American waterway that flows through Brazil, Bolivia, Paraguay, and Argentina, forming part of the Río de la Plata Basin and serving as a vital route for transport, agriculture, and ecosystems in the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69c008f6b5048190a09064116062cf69 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f495c588190b0cfe5bfb3d2c221 completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07d567cb48190839f340041f2300b completed March 22, 2026, 11:37 p.m.
Created at: March 22, 2026, 3:32 p.m.