Triple

T33164487
Position Surface form Disambiguated ID Type / Status
Subject Hugo Becker E848841 entity
Predicate educatedAt P5 FINISHED
Object Conservatoire à rayonnement régional de Lille
The Conservatoire à rayonnement régional de Lille is a prominent French regional conservatory offering advanced training in music, dance, and drama.
E2039588 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: Conservatoire à rayonnement régional de Lille | Statement: [Hugo Becker, educatedAt, Conservatoire à rayonnement régional de Lille]
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: Conservatoire à rayonnement régional de Lille
Triple: [Hugo Becker, educatedAt, Conservatoire à rayonnement régional de Lille]
Generated description
The Conservatoire à rayonnement régional de Lille is a prominent French regional conservatory offering advanced training in music, dance, and drama.

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_69f3495be8808190bbf427733df08aad completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d94b2c648190898ccf4f39b7ad74 completed May 3, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525c041b88190a23e82efad212770 completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a3526724b348190b30a37434afbee97 completed June 19, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_6a35279eb8b08190970ba8ea52ac75a2 completed June 19, 2026, 11:27 a.m.
Created at: May 1, 2026, 1:28 a.m.