Triple

T33629139
Position Surface form Disambiguated ID Type / Status
Subject Chavornay E861499 entity
Predicate hasChurch P15000 FINISHED
Object Reformed Church of Chavornay
The Reformed Church of Chavornay is a Protestant parish church serving the local Reformed community in the municipality of Chavornay, Switzerland.
E2060650 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: Reformed Church of Chavornay | Statement: [Chavornay, hasChurch, Reformed Church of Chavornay]
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: Reformed Church of Chavornay
Triple: [Chavornay, hasChurch, Reformed Church of Chavornay]
Generated description
The Reformed Church of Chavornay is a Protestant parish church serving the local Reformed community in the municipality of Chavornay, Switzerland.

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_69f34981c54c81909b33c3fa2208a52d completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f859cf8c8190a2a0d3d31e4392e7 completed May 3, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36271510a08190960b75f75ddd7f5b completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3627bba8bc81909091699b621fd31b completed June 20, 2026, 5:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3628683bac81908b766d3154f2188d completed June 20, 2026, 5:43 a.m.
Created at: May 1, 2026, 1:41 a.m.