Triple

T34853835
Position Surface form Disambiguated ID Type / Status
Subject Ecclesiastical province of Esztergom-Budapest E1004672 entity
Predicate hasPart P35 FINISHED
Object Diocese of Veszprém
The Diocese of Veszprém is a historic Latin Catholic diocese in western Hungary, centered in the city of Veszprém and known for its medieval roots and role in the country’s ecclesiastical life.
E2132464 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 Veszprém | Statement: [Ecclesiastical province of Esztergom-Budapest, hasPart, Diocese of Veszprém]
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 Veszprém
Triple: [Ecclesiastical province of Esztergom-Budapest, hasPart, Diocese of Veszprém]
Generated description
The Diocese of Veszprém is a historic Latin Catholic diocese in western Hungary, centered in the city of Veszprém and known for its medieval roots and role in the country’s ecclesiastical life.

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_69f76dba76f0819090643cba102c41ec completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78160d3388190822ed8ff3921a8f2 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380f8b68f48190a1bbc2b51f202dcf completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a381054dd7c8190bf1bd04106c4c961 completed June 21, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a3811591560819086763f49d26a5482 completed June 21, 2026, 4:29 p.m.
Created at: May 3, 2026, 4 p.m.