Triple

T4720214
Position Surface form Disambiguated ID Type / Status
Subject María del Carmen Franco y Polo E104745 entity
Predicate familyName P18 FINISHED
Object Polo E317843 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: Polo | Statement: [María del Carmen Franco y Polo, familyName, Polo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polo
Context triple: [María del Carmen Franco y Polo, familyName, Polo]
  • A. Polo chosen
    Polo is the surname of the Venetian merchant and explorer Marco Polo, famed for his extensive travels through Asia and detailed accounts of the Mongol Empire.
  • B. Polo Fields
    Polo Fields is a large multi-use athletic and event venue in San Francisco’s Golden Gate Park, historically used for polo and now popular for running, cycling, concerts, and recreational sports.
  • C. Sportiva
    Sportiva is a tire brand owned by Continental AG, offering budget-friendly tires for everyday driving needs.
  • D. Carreras
    Carreras is a Spanish surname most famously associated with José Carreras, the renowned operatic tenor and member of The Three Tenors.
  • E. Speedway
    Speedway is a small town in Marion County, Indiana, best known as the home of the Indianapolis Motor Speedway and the Indianapolis 500 auto race.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6428e9e081908ce4041183cad13b completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be108fe3b08190b3d306ca4b39860d completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.