Triple

T3099587
Position Surface form Disambiguated ID Type / Status
Subject de Neve E64681 entity
Predicate hasNotableBearer P458 FINISHED
Object Felipe de Neve E10785 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: Felipe de Neve | Statement: [de Neve, hasNotableBearer, Felipe de Neve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Felipe de Neve
Context triple: [de Neve, hasNotableBearer, Felipe de Neve]
  • A. Felipe de Neve chosen
    Felipe de Neve was an 18th-century Spanish colonial governor of California best known for establishing the city of Los Angeles.
  • B. Fernando
    Fernando is the given name of Salgueiro Maia, a key Portuguese military officer who played a leading role in the Carnation Revolution.
  • C. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • D. Nicolás
    Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
  • E. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • 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_69ad857dc98481909e585dc3372e3ed5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada269a9188190aada5b3799d4dfd7 completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f563524819084ae75c024b8291d completed March 12, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:03 p.m.