Triple

T7013278
Position Surface form Disambiguated ID Type / Status
Subject Fernando Alonso E162635 entity
Predicate hasFamilyName P18 FINISHED
Object Alonso E150045 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: Alonso | Statement: [Fernando Alonso, hasFamilyName, Alonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alonso
Context triple: [Fernando Alonso, hasFamilyName, Alonso]
  • A. Alonso chosen
    Alonso is a Spanish given name of Germanic origin, widely used across the Spanish-speaking world and historically borne by numerous nobles, writers, and fictional characters.
  • B. Fernando Alonso
    Fernando Alonso was a prominent Spanish ballet dancer and choreographer who co-founded the Cuban National Ballet and played a key role in developing Cuban ballet.
  • C. Fernando Alonso
    Fernando Alonso is a Spanish Formula One racing driver, widely regarded as one of the sport’s greatest competitors and a multiple-time world champion.
  • D. Perez
    Perez is a biblical figure from the Book of Genesis, known as one of the twin sons of Judah and an ancestor in the lineage leading to King David.
  • E. Adrian Sutil
    Adrian Sutil is a German former Formula One racing driver best known for his long association with the Spyker and Force India teams in the late 2000s and early 2010s.
  • 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_69c6885a127c8190867b059bdccf13ff completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc58b04c8190af4913dbaf43c3d4 completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775656fe48190a9690f5aaca3ba4c completed March 28, 2026, 6:29 a.m.
Created at: March 27, 2026, 2:34 p.m.