Triple

T25856831
Position Surface form Disambiguated ID Type / Status
Subject Maringá E651371 entity
Predicate administrativeDivisionType P1828 FINISHED
Object municipality of Paraná
The municipality of Paraná is a local government unit in the Brazilian state of Paraná, responsible for administering a defined urban and rural territory such as the city of Maringá.
E1697230 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: municipality of Paraná | Statement: [Maringá, administrativeDivisionType, municipality of Paraná]
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: municipality of Paraná
Triple: [Maringá, administrativeDivisionType, municipality of Paraná]
Generated description
The municipality of Paraná is a local government unit in the Brazilian state of Paraná, responsible for administering a defined urban and rural territory such as the city of Maringá.

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_69e7ab39035c8190be15c8aaee1bb858 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f60268b1388190b38c6d70cd028ecf completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da3bc61481909e31e0c43bd01355 completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10dd8a06b881909f8a9ca5d7d77576 completed May 22, 2026, 10:49 p.m.
NED2 Entity disambiguation (via description) batch_6a10de47e1f0819082aae48923ded2c1 completed May 22, 2026, 10:52 p.m.
Created at: April 22, 2026, 8 a.m.