Triple

T23227882
Position Surface form Disambiguated ID Type / Status
Subject Nocturnes for piano E581061 entity
Predicate hasPart P35 FINISHED
Object Nocturne No. 12 in E minor, Op. 107
Nocturne No. 12 in E minor, Op. 107 is a lyrical solo piano piece by Gabriel Fauré, noted for its introspective character and refined harmonic language.
E1603317 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: Nocturne No. 12 in E minor, Op. 107 | Statement: [Nocturnes for piano, hasPart, Nocturne No. 12 in E minor, Op. 107]
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: Nocturne No. 12 in E minor, Op. 107
Triple: [Nocturnes for piano, hasPart, Nocturne No. 12 in E minor, Op. 107]
Generated description
Nocturne No. 12 in E minor, Op. 107 is a lyrical solo piano piece by Gabriel Fauré, noted for its introspective character and refined harmonic language.

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_69f192302e508190b286c284a261f172 completed April 29, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f693aeedc8190a7e6e945fd21f154 completed May 21, 2026, 8:21 p.m.
NEDg Description generation batch_6a0f6a5e0c5c8190af8e682cd9736a6b completed May 21, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6d52d9b88190978d6809eb0adfd1 completed May 21, 2026, 8:38 p.m.
Created at: April 17, 2026, 4:09 p.m.