Triple

T19562387
Position Surface form Disambiguated ID Type / Status
Subject Mariano Boedo E489485 entity
Predicate placeOfBirth P1 FINISHED
Object Salta E624066 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: Salta | Statement: [Mariano Boedo, placeOfBirth, Salta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salta
Context triple: [Mariano Boedo, placeOfBirth, Salta]
  • A. Salta (city) chosen
    Salta is a historic city in northwestern Argentina known for its well-preserved colonial architecture, vibrant cultural traditions, and role as a regional commercial and tourism hub in the Lerma Valley.
  • B. Salta Province
    Salta Province is a large, landlocked region in northwestern Argentina known for its colonial architecture, Andean landscapes, and significant agricultural and wine production.
  • C. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • D. Belén
    Belén is a municipality located in the Rivas Department of southwestern Nicaragua, known for its rural character and agricultural activities.
  • E. Belén
    Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f74fdb08190852461b5d5c954ac completed April 20, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_6a075784e53c81908e7121096b4bd76a completed May 15, 2026, 5:27 p.m.
Created at: April 10, 2026, 1:42 p.m.