Triple

T26001178
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Erfurt E646628 entity
Predicate ecclesiasticalProvince P3089 FINISHED
Object Province of Paderborn
The Province of Paderborn is a Roman Catholic ecclesiastical province in Germany, centered on the Archdiocese of Paderborn and encompassing several suffragan dioceses.
E1705460 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: Province of Paderborn | Statement: [Diocese of Erfurt, ecclesiasticalProvince, Province of Paderborn]
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: Province of Paderborn
Triple: [Diocese of Erfurt, ecclesiasticalProvince, Province of Paderborn]
Generated description
The Province of Paderborn is a Roman Catholic ecclesiastical province in Germany, centered on the Archdiocese of Paderborn and encompassing several suffragan dioceses.

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_69e77e89d5848190b54352cdb74f6029 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f605755bd48190a760f5301eafb3ae completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11079c6f1c8190bc9fa14349bdf6fe completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a1109ba733c819086558e6543a6fed7 completed May 23, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a110a5886208190832eaf3b9986fa76 completed May 23, 2026, 2 a.m.
Created at: April 22, 2026, 9 a.m.