Triple

T23227411
Position Surface form Disambiguated ID Type / Status
Subject Stiffelio E581050 entity
Predicate basedOnAuthor P2806 FINISHED
Object Eugène Bourgeois
Eugène Bourgeois was a French playwright whose work inspired the libretto for Giuseppe Verdi’s opera *Stiffelio*.
E2288526 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: Eugène Bourgeois | Statement: [Stiffelio, basedOnAuthor, Eugène Bourgeois]
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: Eugène Bourgeois
Triple: [Stiffelio, basedOnAuthor, Eugène Bourgeois]
Generated description
Eugène Bourgeois was a French playwright whose work inspired the libretto for Giuseppe Verdi’s opera *Stiffelio*.

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_69e246043c48819089bae72c9a9c306c completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f1922f5b4081908145d66ea7534493 completed April 29, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5a99d19694819099a69828f089631e completed July 17, 2026, 9:08 p.m.
NEDg Description generation batch_6a5a9a34f7c8819094ad056a5782f41b completed July 17, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_6a5a9aab6cdc81909ce1bf98dfb69a95 completed July 17, 2026, 9:12 p.m.
Created at: April 17, 2026, 4:09 p.m.