Triple

T28381241
Position Surface form Disambiguated ID Type / Status
Subject Église Saint-Séverin in Paris (later phases) E718895 entity
Predicate partOf P40 FINISHED
Object Église Saint-Séverin
Église Saint-Séverin is a prominent medieval Gothic church in Paris’s Latin Quarter, noted for its flamboyant architecture, twisted pillar, and rich stained-glass windows.
E1823511 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-Séverin | Statement: [Église Saint-Séverin in Paris (later phases), partOf, Église Saint-Séverin]
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-Séverin
Triple: [Église Saint-Séverin in Paris (later phases), partOf, Église Saint-Séverin]
Generated description
Église Saint-Séverin is a prominent medieval Gothic church in Paris’s Latin Quarter, noted for its flamboyant architecture, twisted pillar, and rich stained-glass windows.

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_69eff6ee5afc8190bd7375a29f0cc6c6 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64cb6c8708190b0a947d7da770920 completed May 2, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac3339cc81908483d4e9562e6c69 completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cadadb2708190ab52e8a3df06eddb completed May 31, 2026, 9:52 p.m.
NED2 Entity disambiguation (via description) batch_6a1cae35e348819097647a4b59628818 completed May 31, 2026, 9:55 p.m.
Created at: April 28, 2026, 1:06 a.m.