Triple

T4783854
Position Surface form Disambiguated ID Type / Status
Subject Martín de Azpilcueta E106428 entity
Predicate hasGivenName P17 FINISHED
Object Martín E194083 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: Martín | Statement: [Martín de Azpilcueta, hasGivenName, Martín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martín
Context triple: [Martín de Azpilcueta, hasGivenName, Martín]
  • A. Martín chosen
    Martín is a masculine given name of Latin origin, commonly used in Spanish-speaking countries and derived from the name Martinus, associated with the Roman god Mars.
  • B. Sebastián
    Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • C. Martín (Hache)
    Martín (Hache) is a 1997 Argentine-Spanish drama film that explores generational conflict, identity, and disillusionment through the strained relationship between a troubled young man and his estranged father in Madrid.
  • D. Alejo
    Alejo is a Spanish given name commonly used as a short form of Alejandro.
  • E. Andrés
    Andrés is a Spanish given name commonly used as the equivalent of Andrew.
  • 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_69bd43f4a9588190bf73e20bc27c03cc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd65ad3a188190872e47e3a3bf504b completed March 20, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be922efb7c8190a7ea9a7c9aa5503d completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:22 p.m.