Triple

T29206986
Position Surface form Disambiguated ID Type / Status
Subject Louis Spohr E740437 entity
Predicate notableWork P4 FINISHED
Object Nonet in F major, Op. 31
The Nonet in F major, Op. 31 is a prominent early Romantic chamber work by Louis Spohr scored for nine instruments, admired for its lyrical melodies and rich ensemble writing.
 E1856226 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: Nonet in F major, Op. 31 | Statement: [Louis Spohr, notableWork, Nonet in F major, Op. 31]
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: Nonet in F major, Op. 31
Triple: [Louis Spohr, notableWork, Nonet in F major, Op. 31]
Generated description
The Nonet in F major, Op. 31 is a prominent early Romantic chamber work by Louis Spohr scored for nine instruments, admired for its lyrical melodies and rich ensemble writing.

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_69f07cb974108190b7e86ca489a6ebb6 completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f664022f0881908c77482eeead99d2 completed May 2, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569c335e8819092760b51b1224dc5 completed June 7, 2026, 12:53 p.m.
NEDg Description generation batch_6a256fb17a888190bde616b95d66ab47 completed June 7, 2026, 1:18 p.m.
NED2 Entity disambiguation (via description) batch_6a257365ca8c8190945e82297e2d8a12 completed June 7, 2026, 1:34 p.m.
Created at: April 28, 2026, 12:09 p.m.