Triple

T15595786
Position Surface form Disambiguated ID Type / Status
Subject Martika E374887 entity
Predicate familyName P18 FINISHED
Object Marrero
Marrero is a Spanish-origin surname commonly found in Hispanic communities, particularly in the Caribbean and Latin America.
 E1167150 NE FINISHED

How this triple was built (4 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: Marrero | Statement: [Martika, familyName, Marrero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marrero
Context triple: [Martika, familyName, Marrero]
  • A. Marrero
    Marrero is a suburban community in southeastern Louisiana located on the west bank of the Mississippi River near New Orleans.
  • B. Boustany
    Boustany is a surname of Lebanese origin notably associated with several prominent political and professional families, particularly in the United States and Lebanon.
  • C. Warley
    Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
  • D. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • E. Crowley
    Crowley is a surname most famously associated with Aleister Crowley, the English occultist, writer, and ceremonial magician.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Marrero
Triple: [Martika, familyName, Marrero]
Generated description
Marrero is a Spanish-origin surname commonly found in Hispanic communities, particularly in the Caribbean and Latin America.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marrero
Target entity description: Marrero is a Spanish-origin surname commonly found in Hispanic communities, particularly in the Caribbean and Latin America.
  • A. Marrero
    Marrero is a suburban community in southeastern Louisiana located on the west bank of the Mississippi River near New Orleans.
  • B. Boustany
    Boustany is a surname of Lebanese origin notably associated with several prominent political and professional families, particularly in the United States and Lebanon.
  • C. Warley
    Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
  • D. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • E. Crowley
    Crowley is a surname most famously associated with Aleister Crowley, the English occultist, writer, and ceremonial magician.
  • F. None of above. chosen

Provenance (5 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5f9db8819083abf80f01f32b3d completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56ca72ec8190a237db843dc6d625 completed May 9, 2026, 3:46 p.m.
NEDg Description generation batch_69ff58a93fb481908cedf981caf1bb23 completed May 9, 2026, 3:54 p.m.
NED2 Entity disambiguation (via description) batch_69ff59718048819086a1d0ba773e9a92 completed May 9, 2026, 3:57 p.m.
Created at: April 10, 2026, 4:12 a.m.