Triple

T23914647
Position Surface form Disambiguated ID Type / Status
Subject Bishop of Opole E602047 entity
Predicate partOf P40 FINISHED
Object Diocese of Opole
The Diocese of Opole is a Roman Catholic ecclesiastical territory in southwestern Poland, centered in the city of Opole and responsible for overseeing the region’s parishes and clergy.
E1625496 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 Opole | Statement: [Bishop of Opole, partOf, Diocese of Opole]
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 Opole
Triple: [Bishop of Opole, partOf, Diocese of Opole]
Generated description
The Diocese of Opole is a Roman Catholic ecclesiastical territory in southwestern Poland, centered in the city of Opole and responsible for overseeing the region’s parishes and clergy.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1ce97f694819087215ed9f18b290e completed April 29, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbceec9f48190a61c9f9c1d3747b1 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbe78822881909e04f037a60db091 completed May 22, 2026, 2:24 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbf0ed7808190b64797da02f8fbac completed May 22, 2026, 2:27 a.m.
Created at: April 17, 2026, 8:39 p.m.