Triple

T16181245
Position Surface form Disambiguated ID Type / Status
Subject Marc Márquez E392686 entity
Predicate placeOfOrigin P3743 FINISHED
Object Cervera E97309 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: Cervera | Statement: [Marc Márquez, placeOfOrigin, Cervera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cervera
Context triple: [Marc Márquez, placeOfOrigin, Cervera]
  • A. Cervera chosen
    Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
  • B. Cabrera de Mar
    Cabrera de Mar is a coastal municipality in the Maresme comarca of Catalonia, Spain, known for its Mediterranean beaches and archaeological heritage.
  • C. Castro Urdiales
    Castro Urdiales is a coastal town in northern Spain known for its medieval architecture, fishing port, and beaches along the Bay of Biscay.
  • D. Spínola
    Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
  • E. Azaña
    Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205c92b48190b7125dbbcff3662e completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffff0022148190bc1810e76cf6d994 completed May 10, 2026, 3:44 a.m.
Created at: April 10, 2026, 5:02 a.m.