Triple

T2232634
Position Surface form Disambiguated ID Type / Status
Subject George Lopez E49202 entity
Predicate voiceActedIn P9616 FINISHED
Object Rio E62222 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: [George Lopez, voiceActedIn, Rio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio
Context triple: [George Lopez, voiceActedIn, Rio]
  • A. Rio chosen
    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.
  • B. Rio
    Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
  • C. Rio
    Rio is a settlement located within the municipality of Elba, an island in the Tyrrhenian Sea off the coast of Italy.
  • 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.

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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc06d26bc8190a85ddb6312d2df08 completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8944c9e0819099aee546cfc1a636 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:47 p.m.