Triple

T30592902
Position Surface form Disambiguated ID Type / Status
Subject Captaincy of Paraíba E778707 entity
Predicate borderedBy P224 FINISHED
Object Captaincy of Rio Grande do Norte
The Captaincy of Rio Grande do Norte was a colonial administrative division of Portuguese Brazil located in the northeastern region along the Atlantic coast.
E1921279 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: Captaincy of Rio Grande do Norte | Statement: [Captaincy of Paraíba, borderedBy, Captaincy of Rio Grande do Norte]
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: Captaincy of Rio Grande do Norte
Triple: [Captaincy of Paraíba, borderedBy, Captaincy of Rio Grande do Norte]
Generated description
The Captaincy of Rio Grande do Norte was a colonial administrative division of Portuguese Brazil located in the northeastern region along the Atlantic coast.

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_69f224a1570c8190a85d3ac330479a79 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6897c9b2881909521988f496bdf95 completed May 2, 2026, 11:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2857151d748190896ba6e26c53ef89 completed June 9, 2026, 6:10 p.m.
NEDg Description generation batch_6a285842b7508190888aecb939ff75d1 completed June 9, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2858b75ed08190b2c62775ccdf9fd3 completed June 9, 2026, 6:17 p.m.
Created at: April 29, 2026, 8:24 p.m.