Triple

T31602976
Position Surface form Disambiguated ID Type / Status
Subject Maud Tortelier E806396 entity
Predicate motherOf P120 FINISHED
Object Yan Pascal Tortelier
Yan Pascal Tortelier is a French conductor and violinist known for his interpretations of orchestral and symphonic repertoire with major ensembles worldwide.
E2292334 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: Yan Pascal Tortelier | Statement: [Maud Tortelier, motherOf, Yan Pascal Tortelier]
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: Yan Pascal Tortelier
Triple: [Maud Tortelier, motherOf, Yan Pascal Tortelier]
Generated description
Yan Pascal Tortelier is a French conductor and violinist known for his interpretations of orchestral and symphonic repertoire with major ensembles worldwide.

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_69f348d54ccc8190a03b5df9a2b40b25 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a86d4ad08190b3372558c9f544a6 completed May 3, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5ce418ddf88190a85416a79f7225fe completed July 19, 2026, 2:50 p.m.
NEDg Description generation batch_6a672da79a7481909b324f18b8d2649f completed July 27, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a683a3f71d08190a2b0af62998f9352 completed July 28, 2026, 5:12 a.m.
Created at: April 30, 2026, 10:33 p.m.