Triple

T14810822
Position Surface form Disambiguated ID Type / Status
Subject Emiliano Martínez E348172 entity
Predicate placeOfBirth P1 FINISHED
Object Mar del Plata E304269 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: Mar del Plata | Statement: [Emiliano Martínez, placeOfBirth, Mar del Plata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mar del Plata
Context triple: [Emiliano Martínez, placeOfBirth, Mar del Plata]
  • A. Mar del Plata chosen
    Mar del Plata is a major Argentine Atlantic coastal city renowned as a popular beach resort and tourist destination.
  • B. Bahía Blanca
    Bahía Blanca is a major port city in southern Buenos Aires Province, Argentina, known for its industrial activity and strategic location on the Atlantic coast.
  • C. Buenos Aires
    Buenos Aires is the capital and largest city of Argentina, known for its rich European-influenced culture, tango music and dance, and vibrant urban life.
  • D. La Plata
    La Plata, historically known as the city of Sucre in present-day Bolivia, is a colonial-era Andean city that served as an important administrative and judicial center of the Spanish Empire in South America.
  • E. La Plata
    La Plata is the planned capital city of Argentina’s Buenos Aires Province, known for its distinctive diagonal street grid and cultural and educational institutions.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf35a5e081909321193ef37099d1 completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b47389c8190ab0a46e3b4653a2a completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:46 a.m.