Triple

T29354249
Position Surface form Disambiguated ID Type / Status
Subject Archdiocese of Kampala E744393 entity
Predicate isMetropolitanSeeFor P20454 FINISHED
Object Diocese of Masaka
The Diocese of Masaka is a Roman Catholic ecclesiastical territory in Uganda that functions as a suffragan diocese under the Archdiocese of Kampala.
E1869854 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: Diocese of Masaka | Statement: [Archdiocese of Kampala, isMetropolitanSeeFor, Diocese of Masaka]
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: Diocese of Masaka
Triple: [Archdiocese of Kampala, isMetropolitanSeeFor, Diocese of Masaka]
Generated description
The Diocese of Masaka is a Roman Catholic ecclesiastical territory in Uganda that functions as a suffragan diocese under the Archdiocese of Kampala.

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_69f0a79a2d748190bc30abd469298b37 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f6695de4b08190983486979828acf7 completed May 2, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0f9b5848190838cacda83a6617e completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f511e960819093280d75cefec6fd completed June 7, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_6a25f92f6744819093a671170bd83115 completed June 7, 2026, 11:05 p.m.
Created at: April 28, 2026, 2:09 p.m.