Triple

T28002758
Position Surface form Disambiguated ID Type / Status
Subject École Freudienne de Paris E707189 entity
Predicate hadNotableMember P304 FINISHED
Object Serge Leclaire
Serge Leclaire was a prominent French psychoanalyst and close collaborator of Jacques Lacan, known for his influential contributions to Lacanian theory and clinical practice.
E2240709 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: Serge Leclaire | Statement: [École Freudienne de Paris, hadNotableMember, Serge Leclaire]
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: Serge Leclaire
Triple: [École Freudienne de Paris, hadNotableMember, Serge Leclaire]
Generated description
Serge Leclaire was a prominent French psychoanalyst and close collaborator of Jacques Lacan, known for his influential contributions to Lacanian theory and clinical practice.

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_69ef96b980d88190a753b2f9a978595a completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63bd2dc3c81908ee2471fa32c7841 completed May 2, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d6582b148190bc4595659faf4828 completed June 28, 2026, 8:07 a.m.
NEDg Description generation batch_6a40d88e2bf48190ba6b3040ea8559b8 completed June 28, 2026, 8:17 a.m.
NED2 Entity disambiguation (via description) batch_6a40d8f9142081908a71318aad0e4c8b completed June 28, 2026, 8:19 a.m.
Created at: April 27, 2026, 7:58 p.m.