Triple

T5220852
Position Surface form Disambiguated ID Type / Status
Subject Province of Livorno E117863 entity
Predicate contains P35 FINISHED
Object Rio E146505 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: [Province of Livorno, contains, Rio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio
Context triple: [Province of Livorno, contains, Rio]
  • A. Rio
    Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
  • B. Rio chosen
    Rio is a settlement located within the municipality of Elba, an island in the Tyrrhenian Sea off the coast of Italy.
  • C. 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.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7ab846548190bcd2c5cd238f6cd9 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf29008b38819084e59078210626b2 completed March 21, 2026, 11:25 p.m.
Created at: March 20, 2026, 1:48 p.m.