Triple

T32200865
Position Surface form Disambiguated ID Type / Status
Subject Great Shefford E822530 entity
Predicate hasChurch P15000 FINISHED
Object Church of Saint Mary
The Church of Saint Mary is a historic parish church serving the local Anglican community in the village of Great Shefford, England.
 E1998753 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: Church of Saint Mary | Statement: [Great Shefford, hasChurch, Church of Saint Mary]
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: Church of Saint Mary
Triple: [Great Shefford, hasChurch, Church of Saint Mary]
Generated description
The Church of Saint Mary is a historic parish church serving the local Anglican community in the village of Great Shefford, England.

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_69f349093174819086e633c190a51aa8 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb3bcbe88190ab5511323b95e6b7 completed May 3, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46c42fe48190b4cdfbaa8c156659 completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f4831a32c8190ad20aa36509c985f completed June 15, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_6a2f48982324819085c67bfe1168b66d completed June 15, 2026, 12:34 a.m.
Created at: May 1, 2026, 12:36 a.m.