Triple

T35762592
Position Surface form Disambiguated ID Type / Status
Subject Les Lilas E1033915 entity
Predicate hasLandmark P105 FINISHED
Object Église Saint-Germain-des-Prés des Lilas
Église Saint-Germain-des-Prés des Lilas is a Catholic church serving as a notable religious and architectural landmark in the Paris suburb of Les Lilas, France.
E2154630 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-Germain-des-Prés des Lilas | Statement: [Les Lilas, hasLandmark, Église Saint-Germain-des-Prés des Lilas]
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-Germain-des-Prés des Lilas
Triple: [Les Lilas, hasLandmark, Église Saint-Germain-des-Prés des Lilas]
Generated description
Église Saint-Germain-des-Prés des Lilas is a Catholic church serving as a notable religious and architectural landmark in the Paris suburb of Les Lilas, France.

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_69f76e13edd081909101629aa829c4ad completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1c562848190ba1fe4f9cb7efa87 completed May 3, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885fc02cc8190abbc649706e5c4a4 completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a3887948e148190873b6efc5735127b completed June 22, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a388849bf348190ba71468323566c56 completed June 22, 2026, 12:56 a.m.
Created at: May 3, 2026, 4:06 p.m.