Triple

T33919942
Position Surface form Disambiguated ID Type / Status
Subject Suite No. 1 in D minor, Op. 43 E869572 entity
Predicate hasPart P35 FINISHED
Object Divertimento
Divertimento is a light, typically multi-movement classical composition known for its informal, entertaining character, often written for a small ensemble.
E2073648 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: Divertimento | Statement: [Suite No. 1 in D minor, Op. 43, hasPart, Divertimento]
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: Divertimento
Triple: [Suite No. 1 in D minor, Op. 43, hasPart, Divertimento]
Generated description
Divertimento is a light, typically multi-movement classical composition known for its informal, entertaining character, often written for a small ensemble.

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_69f349992c508190aa4afa24a086cc8c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f701e7e76c8190a26a88cd6f6d38a8 completed May 3, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a368251b7148190a82672a8e7d57ad6 completed June 20, 2026, 12:06 p.m.
NEDg Description generation batch_6a36833628008190be2fee19069cfad6 completed June 20, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_6a36848248c081909b5ab57a8c3accc6 completed June 20, 2026, 12:16 p.m.
Created at: May 1, 2026, 1:49 a.m.