Triple

T28794400
Position Surface form Disambiguated ID Type / Status
Subject Catholic Church in Vietnam E727045 entity
Predicate hasPart P35 FINISHED
Object Diocese of Thủ Dầu Một
The Diocese of Thủ Dầu Một is a territorial jurisdiction of the Roman Catholic Church located in and serving the faithful of the Thủ Dầu Một area in Vietnam.
E1874307 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 Thủ Dầu Một | Statement: [Catholic Church in Vietnam, hasPart, Diocese of Thủ Dầu Một]
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 Thủ Dầu Một
Triple: [Catholic Church in Vietnam, hasPart, Diocese of Thủ Dầu Một]
Generated description
The Diocese of Thủ Dầu Một is a territorial jurisdiction of the Roman Catholic Church located in and serving the faithful of the Thủ Dầu Một area in Vietnam.

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_69f0319b7c44819085736bcc256185e6 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f6587d47cc81908964bd2748c2e90f completed May 2, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d3e631c81909c1b882ca00bf156 completed June 8, 2026, 2:47 a.m.
NEDg Description generation batch_6a2632d0c8bc8190af26fa5501bba081 completed June 8, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_6a26367d4ccc8190aa6cee70880352ed completed June 8, 2026, 3:26 a.m.
Created at: April 28, 2026, 6:24 a.m.