Triple

T28330668
Position Surface form Disambiguated ID Type / Status
Subject Ménilmontant E717529 entity
Predicate adjacentTo P224 FINISHED
Object Belleville neighborhood
The Belleville neighborhood is a historically working-class, multicultural district in northeastern Paris known for its vibrant street life, street art, and panoramic views from Parc de Belleville.
E1813535 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: Belleville neighborhood | Statement: [Ménilmontant, adjacentTo, Belleville neighborhood]
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: Belleville neighborhood
Triple: [Ménilmontant, adjacentTo, Belleville neighborhood]
Generated description
The Belleville neighborhood is a historically working-class, multicultural district in northeastern Paris known for its vibrant street life, street art, and panoramic views from Parc de Belleville.

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_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bce044c81908c397f6eb05e74c1 completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627b7149481908457a97233ccfa45 completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a16294860f08190adf72188a0fe0c18 completed May 26, 2026, 11:14 p.m.
NED2 Entity disambiguation (via description) batch_6a162a96c8c48190a4987d51fa9ea9ee completed May 26, 2026, 11:19 p.m.
Created at: April 28, 2026, 12:32 a.m.