Triple

T35038182
Position Surface form Disambiguated ID Type / Status
Subject Julius Klengel E1010985 entity
Predicate notableWork P4 FINISHED
Object Technical Studies for cello, Op. 31
Technical Studies for cello, Op. 31 is a widely used collection of advanced cello etudes by Julius Klengel, designed to develop and refine professional-level technique.
E2124267 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: Technical Studies for cello, Op. 31 | Statement: [Julius Klengel, notableWork, Technical Studies for cello, 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: Technical Studies for cello, Op. 31
Triple: [Julius Klengel, notableWork, Technical Studies for cello, Op. 31]
Generated description
Technical Studies for cello, Op. 31 is a widely used collection of advanced cello etudes by Julius Klengel, designed to develop and refine professional-level technique.

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_69f76dcea02c81908542a223f6d5059f completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7858f4eac8190a71bc6fddd380cda completed May 3, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c62faa8081909b3de122e1bb85ac completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c704e7c88190a1e12c6aa9375992 completed June 21, 2026, 11:12 a.m.
NED2 Entity disambiguation (via description) batch_6a37c82ccd3c8190ac151138acfa58df completed June 21, 2026, 11:17 a.m.
Created at: May 3, 2026, 4:01 p.m.