Triple

T25663172
Position Surface form Disambiguated ID Type / Status
Subject St Mary’s Church, Morpeth E643440 entity
Predicate deanery P19542 FINISHED
Object Deanery of Morpeth
The Deanery of Morpeth is an administrative division of the Church of England that oversees a group of parishes in and around the town of Morpeth in Northumberland.
E1689541 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: Deanery of Morpeth | Statement: [St Mary’s Church, Morpeth, deanery, Deanery of Morpeth]
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: Deanery of Morpeth
Triple: [St Mary’s Church, Morpeth, deanery, Deanery of Morpeth]
Generated description
The Deanery of Morpeth is an administrative division of the Church of England that oversees a group of parishes in and around the town of Morpeth in Northumberland.

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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5faf125388190bf20dd812f1a2632 completed May 2, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c152bcc48190bb544e464d848bf5 completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c2d522988190bc01978dc5ef272f completed May 22, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a10c36b20a0819084d94066362937ee completed May 22, 2026, 8:58 p.m.
Created at: April 21, 2026, 6:57 p.m.