Triple

T28804215
Position Surface form Disambiguated ID Type / Status
Subject Julio Argentino Roca E727327 entity
Predicate succeededBy P78 FINISHED
Object Miguel Juárez Celman
Miguel Juárez Celman was an Argentine lawyer and politician who served as President of Argentina from 1886 to 1890, leading a period of rapid economic expansion that ended amid political and financial crisis.
E2010173 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: Miguel Juárez Celman | Statement: [Julio Argentino Roca, succeededBy, Miguel Juárez Celman]
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: Miguel Juárez Celman
Triple: [Julio Argentino Roca, succeededBy, Miguel Juárez Celman]
Generated description
Miguel Juárez Celman was an Argentine lawyer and politician who served as President of Argentina from 1886 to 1890, leading a period of rapid economic expansion that ended amid political and financial crisis.

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_69f0319c38948190bca746ad60fd25ba completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658aceef4819087f7b9298bc53cd3 completed May 2, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a34702900308190ad4468e4ceff59f4 completed June 18, 2026, 10:24 p.m.
NEDg Description generation batch_6a3470d2101c8190bc7c6a246420a06a completed June 18, 2026, 10:27 p.m.
NED2 Entity disambiguation (via description) batch_6a34714da9c481908ef8aec2f25b5024 completed June 18, 2026, 10:29 p.m.
Created at: April 28, 2026, 6:28 a.m.