Triple

T11290345
Position Surface form Disambiguated ID Type / Status
Subject John Romero E267307 entity
Predicate givenName P17 FINISHED
Object Alfonso E162427 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: Alfonso | Statement: [John Romero, givenName, Alfonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alfonso
Context triple: [John Romero, givenName, Alfonso]
  • A. Alfonso chosen
    Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
  • B. Alfonso Royal
    Alfonso Royal is a central fictional figure around whom the narrative of "The Royal Family" revolves.
  • C. Alfonso the Battler
    Alfonso the Battler was a 12th-century King of Aragon and Navarre renowned for his relentless military campaigns during the Reconquista against Muslim-ruled territories in the Iberian Peninsula.
  • D. X Alfonso
    X Alfonso is a Cuban musician and cultural entrepreneur best known for his influential role in Havana’s contemporary arts scene.
  • E. Alfonso d’Aragona
    Alfonso d’Aragona was a Neapolitan nobleman and member of the Aragonese royal dynasty of Naples, active in the late 15th and early 16th centuries.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98875a08190b8509fe55e49d52d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0ce0a508190a2f44cbe812b5f17 completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:32 p.m.