Triple

T706298
Position Surface form Disambiguated ID Type / Status
Subject Mariano Rivera E14106 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: [Mariano Rivera, familyName, Rivera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rivera
Context triple: [Mariano Rivera, familyName, Rivera]
  • A. Rivera chosen
    Rivera is a common Spanish-language surname borne by numerous notable figures across sports, politics, arts, and entertainment.
  • B. Río de los Remedios
    Río de los Remedios is a Metrobús station in Mexico City that serves as the northern terminus of Line 5 in the city’s bus rapid transit system.
  • C. Illapel River
    The Illapel River is a watercourse in Chile’s Coquimbo Region that flows through the Choapa Province, supporting local agriculture and communities in a semi-arid landscape.
  • D. Río Negro
    Río Negro is a major river in Argentine Patagonia known for irrigating fertile valleys and supporting agriculture and settlements across the region.
  • E. Grande River
    The Grande River is a watercourse in Chile’s Limarí Province that contributes to the region’s agricultural irrigation and local watershed.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a54607f08190b3ee4805f2ea4b2f completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4bf512bc81908ff403ce87337a0d completed March 7, 2026, 4:01 p.m.
Created at: March 1, 2026, 7:36 p.m.