Triple

T9762321
Position Surface form Disambiguated ID Type / Status
Subject Mamá Coco E236698 entity
Predicate familyName P18 FINISHED
Object Rivera E114090 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: Rivera | Statement: [Mamá Coco, familyName, Rivera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rivera
Context triple: [Mamá Coco, familyName, Rivera]
  • A. Rivera chosen
    Rivera is a common Spanish-language surname borne by numerous notable figures across sports, politics, arts, and entertainment.
  • B. Rivera
    Rivera is a city in northern Uruguay, located on the border with Brazil, known for its binational urban area shared with the Brazilian city of Santana do Livramento.
  • C. Río
    Río is a central character in the Spanish television series "La Casa de Papel" ("Money Heist"), known as a young, talented hacker and member of the Professor's heist crew.
  • D. La Plata River
    La Plata River is a major river in Puerto Rico that flows through several municipalities, including Bayamón, before emptying into the Atlantic Ocean.
  • E. La Plata River
    La Plata River is a watercourse known for flowing through regions inhabited by the prized game fish dorado in South America.
  • 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda04c70108190a8ed09eb6f2a124e completed April 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5a4a88c8190bac0a2bff02804dc completed April 5, 2026, 3:23 a.m.
Created at: March 30, 2026, 8:25 p.m.