Triple
T29180127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suite in B-flat major, HWV 434 |
E739723
|
entity |
| Predicate | workTitle |
P24259
|
FINISHED |
| Object |
Suite in B-flat major
Suite in B-flat major (HWV 434) is a keyboard suite by George Frideric Handel, best known for its expressive Sarabande that has been widely used and adapted in later music and media.
|
E1852970
|
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: Suite in B-flat major | Statement: [Suite in B-flat major, HWV 434, workTitle, Suite in B-flat major]
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: Suite in B-flat major Triple: [Suite in B-flat major, HWV 434, workTitle, Suite in B-flat major]
Generated description
Suite in B-flat major (HWV 434) is a keyboard suite by George Frideric Handel, best known for its expressive Sarabande that has been widely used and adapted in later music and media.
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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f663444268819088b7976a7295d57a |
completed | May 2, 2026, 8:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25507c108c8190abb5c58b12a7f322 |
completed | June 7, 2026, 11:05 a.m. |
| NEDg | Description generation | batch_6a25549d699c8190ae6875c3b3ca5786 |
completed | June 7, 2026, 11:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2558a79dbc8190aab5673a45547d65 |
completed | June 7, 2026, 11:40 a.m. |
Created at: April 28, 2026, 11:56 a.m.