Triple

T26676552
Position Surface form Disambiguated ID Type / Status
Subject Roman Catholic Diocese of Maliana E672471 entity
Predicate firstBishop P16625 FINISHED
Object Norberto do Amaral
Norberto do Amaral is a Timorese Roman Catholic prelate who became the inaugural bishop of the Diocese of Maliana in East Timor.
E1809825 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: Norberto do Amaral | Statement: [Roman Catholic Diocese of Maliana, firstBishop, Norberto do Amaral]
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: Norberto do Amaral
Triple: [Roman Catholic Diocese of Maliana, firstBishop, Norberto do Amaral]
Generated description
Norberto do Amaral is a Timorese Roman Catholic prelate who became the inaugural bishop of the Diocese of Maliana in East Timor.

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_69eecda13424819092b17942c4edf722 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f61704491c8190a8fd03a9f9ccc7be completed May 2, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606e71cac81908efefeb5ca2e6af0 completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a160b9720f481909468de84b921f226 completed May 26, 2026, 9:07 p.m.
NED2 Entity disambiguation (via description) batch_6a160d9ea5688190be4b7377a459f367 completed May 26, 2026, 9:16 p.m.
Created at: April 27, 2026, 3:16 a.m.