Triple

T28002683
Position Surface form Disambiguated ID Type / Status
Subject Société psychanalytique de Paris E707188 entity
Predicate foundedBy P104 FINISHED
Object Sacha Nacht
Sacha Nacht was a prominent French psychoanalyst and psychiatrist who played a key role in establishing and institutionalizing psychoanalysis in France in the mid-20th century.
 E1801193 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: Sacha Nacht | Statement: [Société psychanalytique de Paris, foundedBy, Sacha Nacht]
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: Sacha Nacht
Triple: [Société psychanalytique de Paris, foundedBy, Sacha Nacht]
Generated description
Sacha Nacht was a prominent French psychoanalyst and psychiatrist who played a key role in establishing and institutionalizing psychoanalysis in France in the mid-20th century.

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_6a15b898c9d481909de9138a085665b0 completed May 26, 2026, 3:13 p.m.
NEDg Description generation batch_6a15bf8d3b5c8190a378572c365b3a95 completed May 26, 2026, 3:43 p.m.
NED2 Entity disambiguation (via description) batch_6a15c090b6b48190863939760871e49c completed May 26, 2026, 3:47 p.m.
Created at: April 27, 2026, 7:58 p.m.