Triple

T26517446
Position Surface form Disambiguated ID Type / Status
Subject Kirkmuirhill E669856 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object Our Lady and St John Catholic Church
Our Lady and St John Catholic Church is a Roman Catholic parish church serving the local community in Kirkmuirhill, Scotland.
E1728409 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: Our Lady and St John Catholic Church | Statement: [Kirkmuirhill, hasReligiousBuilding, Our Lady and St John Catholic Church]
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: Our Lady and St John Catholic Church
Triple: [Kirkmuirhill, hasReligiousBuilding, Our Lady and St John Catholic Church]
Generated description
Our Lady and St John Catholic Church is a Roman Catholic parish church serving the local community in Kirkmuirhill, Scotland.

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_69eeb31b6dcc8190b30632dc3928a0c0 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613beb3a48190ae3fa9faf15f7122 completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb439f70819091a90baa84bd8567 completed May 23, 2026, 2:35 p.m.
NEDg Description generation batch_6a11bbb2cbd0819085f26c79639d1634 completed May 23, 2026, 2:37 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf9449b08190bcaff036e81d9392 completed May 23, 2026, 2:54 p.m.
Created at: April 27, 2026, 1:24 a.m.