Triple

T36862099
Position Surface form Disambiguated ID Type / Status
Subject Provincia de San Luis E910969 entity
Predicate hasDepartment P35 FINISHED
Object Departamento Juan Martín de Pueyrredón
Departamento Juan Martín de Pueyrredón is an administrative department that includes the provincial capital city of San Luis in central Argentina.
E2202105 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: Departamento Juan Martín de Pueyrredón | Statement: [Provincia de San Luis, hasDepartment, Departamento Juan Martín de Pueyrredón]
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: Departamento Juan Martín de Pueyrredón
Triple: [Provincia de San Luis, hasDepartment, Departamento Juan Martín de Pueyrredón]
Generated description
Departamento Juan Martín de Pueyrredón is an administrative department that includes the provincial capital city of San Luis in central Argentina.

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_69f76e80f6f0819091cba8e19b269615 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfd0b33c81908526295253a7ddee completed May 3, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfadea3988190a49c19df6d02586c completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfd5aa9788190af71bb5c6a7af107 completed June 26, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3e02af021481908d97618a61ce8d54 completed June 26, 2026, 4:40 a.m.
Created at: May 3, 2026, 4:13 p.m.