Triple

T6285207
Position Surface form Disambiguated ID Type / Status
Subject Diego Simeone E140882 entity
Predicate managedClub P3239 FINISHED
Object San Lorenzo de Almagro E517799 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: San Lorenzo de Almagro | Statement: [Diego Simeone, managedClub, San Lorenzo de Almagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Lorenzo de Almagro
Context triple: [Diego Simeone, managedClub, San Lorenzo de Almagro]
  • A. San Lorenzo
    San Lorenzo is a coastal municipality on the island province of Guimaras in the Philippines, known for its rural communities and agricultural landscape.
  • B. San Lorenzo
    San Lorenzo is a municipality in the central-eastern region of Puerto Rico known for its rural landscapes and small-town character.
  • C. San Lorenzo
    San Lorenzo is an upscale commercial and residential district in Makati, Metro Manila, known for its gated villages, shopping centers, and proximity to the central business area.
  • D. San Lorenzo
    San Lorenzo is an unincorporated community in Alameda County, California, located in the East Bay region of the San Francisco Bay Area.
  • E. San Lorenzo chosen
    San Lorenzo is one of Argentina’s traditional “big five” football clubs, based in Buenos Aires and known for its passionate fan base and historic success in domestic and international competitions.
  • 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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063fc906481908283c6c50a212515 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5196defc08190810c6d208ade918b completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:26 p.m.