Triple

T26241689
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Cádiz y Ceuta E656330 entity
Predicate previousBishop P59715 FINISHED
Object Antonio Ceballos Atienza
Antonio Ceballos Atienza is a Spanish Roman Catholic prelate who served as bishop in southern Spain, including the Diocese of Cádiz y Ceuta.
E1851527 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: Antonio Ceballos Atienza | Statement: [Diocese of Cádiz y Ceuta, previousBishop, Antonio Ceballos Atienza]
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: Antonio Ceballos Atienza
Triple: [Diocese of Cádiz y Ceuta, previousBishop, Antonio Ceballos Atienza]
Generated description
Antonio Ceballos Atienza is a Spanish Roman Catholic prelate who served as bishop in southern Spain, including the Diocese of Cádiz y Ceuta.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60d8f7f9c8190bb8cb8f8ac4c0ca5 completed May 2, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25377d741c8190875f79e488fa2bae completed June 7, 2026, 9:18 a.m.
NEDg Description generation batch_6a253bf87598819087116abf2274d649 completed June 7, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_6a25470a98f48190b7afa02e39675cc3 completed June 7, 2026, 10:25 a.m.
Created at: April 26, 2026, 9:03 p.m.