Triple

T30160636
Position Surface form Disambiguated ID Type / Status
Subject Audinghen E766652 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object Église Saint-Pierre d’Audinghen
Église Saint-Pierre d’Audinghen is a modernist Catholic church in the coastal village of Audinghen in northern France, noted for its distinctive post–World War II architecture and seaside setting.
E1900504 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: Église Saint-Pierre d’Audinghen | Statement: [Audinghen, hasReligiousBuilding, Église Saint-Pierre d’Audinghen]
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: Église Saint-Pierre d’Audinghen
Triple: [Audinghen, hasReligiousBuilding, Église Saint-Pierre d’Audinghen]
Generated description
Église Saint-Pierre d’Audinghen is a modernist Catholic church in the coastal village of Audinghen in northern France, noted for its distinctive post–World War II architecture and seaside setting.

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_69f2247a968881909d79c18f2bfcb275 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67eda72fc819097a2448757a138e8 completed May 2, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274cc73eb481909555e2886d37751d completed June 8, 2026, 11:14 p.m.
NEDg Description generation batch_6a274d5a67ec81909f2e7f0b7a91a280 completed June 8, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_6a274dbbc3e481909601c15e6843fe92 completed June 8, 2026, 11:18 p.m.
Created at: April 29, 2026, 7:21 p.m.