Triple

T35756529
Position Surface form Disambiguated ID Type / Status
Subject Symbolist theatre E1033456 entity
Predicate associatedWith P37 FINISHED
Object Aurélien Lugné-Poe
Aurélien Lugné-Poe was a pioneering French actor, director, and theatre manager who helped establish modern Symbolist and avant-garde theatre in the late 19th and early 20th centuries.
E2160239 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: Aurélien Lugné-Poe | Statement: [Symbolist theatre, associatedWith, Aurélien Lugné-Poe]
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: Aurélien Lugné-Poe
Triple: [Symbolist theatre, associatedWith, Aurélien Lugné-Poe]
Generated description
Aurélien Lugné-Poe was a pioneering French actor, director, and theatre manager who helped establish modern Symbolist and avant-garde theatre in the late 19th and early 20th centuries.

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_69f76e1262f48190a313318665acc189 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a19b531481909ced9ab9b852f284 completed May 3, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4d777e881909fa0299de1dd7754 completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a59a0184819080e951c76a48eb0c completed June 22, 2026, 3:01 a.m.
NED2 Entity disambiguation (via description) batch_6a38a63caecc8190a4ac4eb8af4bb18b completed June 22, 2026, 3:04 a.m.
Created at: May 3, 2026, 4:06 p.m.