Triple

T34145259
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Huajuapan de León E875835 entity
Predicate hasBishop P10284 FINISHED
Object Miguel Ángel Castro Muñoz
Miguel Ángel Castro Muñoz is a Roman Catholic prelate who serves as the bishop of the Diocese of Huajuapan de León in Mexico.
E2086300 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 Ángel Castro Muñoz | Statement: [Diocese of Huajuapan de León, hasBishop, Miguel Ángel Castro Muñoz]
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 Ángel Castro Muñoz
Triple: [Diocese of Huajuapan de León, hasBishop, Miguel Ángel Castro Muñoz]
Generated description
Miguel Ángel Castro Muñoz is a Roman Catholic prelate who serves as the bishop of the Diocese of Huajuapan de León in Mexico.

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_69f349abaa508190a820f206620efddc completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70f8fd0348190bbf808abc0d350e9 completed May 3, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36cc74624c8190a4e037084467f9e3 completed June 20, 2026, 5:23 p.m.
NEDg Description generation batch_6a36cdae40b88190885e36cb022ca093 completed June 20, 2026, 5:28 p.m.
NED2 Entity disambiguation (via description) batch_6a36cef73ae4819087a176198cd876b0 completed June 20, 2026, 5:33 p.m.
Created at: May 1, 2026, 1:54 a.m.