Triple

T33534426
Position Surface form Disambiguated ID Type / Status
Subject G. I. Gurdjieff E858879 entity
Predicate influenced P9 FINISHED
Object Maurice Nicoll
Maurice Nicoll was a British psychiatrist, writer, and prominent teacher of the Fourth Way who helped interpret and disseminate the psychological and spiritual ideas of Gurdjieff and Ouspensky.
E2066740 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: Maurice Nicoll | Statement: [G. I. Gurdjieff, influenced, Maurice Nicoll]
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: Maurice Nicoll
Triple: [G. I. Gurdjieff, influenced, Maurice Nicoll]
Generated description
Maurice Nicoll was a British psychiatrist, writer, and prominent teacher of the Fourth Way who helped interpret and disseminate the psychological and spiritual ideas of Gurdjieff and Ouspensky.

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_69f34978caf4819083f90eba4944d8e8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f6bfd71c8190addc188afc9e8176 completed May 3, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3665638c9c8190bdc3bd12dbc35115 completed June 20, 2026, 10:03 a.m.
NEDg Description generation batch_6a3665efbb448190922dc19f5096ddeb completed June 20, 2026, 10:05 a.m.
NED2 Entity disambiguation (via description) batch_6a36668c38748190862e1994968ce873 completed June 20, 2026, 10:08 a.m.
Created at: May 1, 2026, 1:39 a.m.