Triple

T21586396
Position Surface form Disambiguated ID Type / Status
Subject Martín Miguel de Güemes E532661 entity
Predicate givenName P17 FINISHED
Object Martín Miguel NE NERFINISHED

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 Miguel | Statement: [Martín Miguel de Güemes, givenName, Martín Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martín Miguel
Context triple: [Martín Miguel de Güemes, givenName, Martín Miguel]
  • A. Martín Miguel de Güemes chosen
    Martín Miguel de Güemes was an Argentine military leader and folk hero who led guerrilla forces in the northwest to defend the revolution during the Argentine War of Independence.
  • B. José Gervasio
    José Gervasio is the given name of José Gervasio Artigas, the national hero of Uruguay and a key leader in the country’s struggle for independence.
  • C. San Martín
    San Martín is a city in western Argentina that serves as an important agricultural and commercial center within Mendoza Province, particularly known for its role in the regional wine industry.
  • D. San Martín
    San Martín is an important industrial and residential city in the Greater Buenos Aires metropolitan area of Argentina.
  • E. San Martín
    San Martín is a municipality in El Salvador known for its proximity to the capital and its role as a growing urban and commercial center in the San Salvador metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb6137fc8190840b7c1275e62a1d completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.